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Spotify
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  • Spotify is seeking a Group Product Manager to lead the transformation... Read More
    Spotify is seeking a Group Product Manager to lead the transformation of its messaging system, critical for delivering over 70 billion impressions annually. This role involves setting the vision, strategy, and roadmap for innovative Messaging capabilities across multiple channels. The ideal candidate will have experience in leading product strategy and a deep understanding of messaging governance, balancing user experience and business outcomes. This position operates within the EST and GMT time zones for collaboration. #J-18808-Ljbffr Read Less
  • This position sits at the heart of Spotify's Content Platform, respons... Read More
    This position sits at the heart of Spotify's Content Platform, responsible for the systems that define, structure, and govern all content across the platform. Our mission is to provide a trusted, consistent source of truth so content can be reliably managed and reused across every Spotify experience. We build and operate the core systems and workflows that ensure content is accurate, complete, and available; from APIs and life cycle orchestration through to content quality and integrity. As Spotify's content ecosystem continues to grow in scale and complexity – across new formats, use cases, and regulatory environments – this domain plays a critical role in ensuring we scale intentionally while maintaining the trust and quality our users and creators expect. We're now seeking a Director of Engineering to lead this domain – shaping its technical direction, developing teams, and evolving the systems that underpin Spotify's global content platform. What You'll Do Lead and develop multiple engineering teams through engineering managers, supporting their growth and impact Own and drive the technical strategy for a critical platform domain, aligning with broader company and platform goals Enable teams across Spotify to build product experiences efficiently by improving the underlying catalog systems Guide the evolution and modernization of complex, legacy systems into scalable, reliable architecture Partner closely with product and cross-functional leaders to align priorities and drive execution Improve system reliability and reduce operational friction in workflows that directly impact content availability Identify and apply opportunities for automation and AI to improve data quality and engineering productivity Build a strong, inclusive engineering culture where teams continuously improve how they work and deliver Develop and execute a long‑term roadmap balancing immediate priorities with strategic investments Who You Are You have experience leading engineering organizations through other leaders and scaling teams effectively You have worked on complex, data‑intensive systems where accuracy, consistency, and reliability at scale are critical You are confident in system design and architectural decision‑making in distributed systems You are comfortable navigating ambiguity and making trade‑offs in high‑pressure, high‑impact environments You have experience evolving legacy systems and guiding long‑term platform transformations You influence effectively across engineering, product, and business stakeholders You have experience leading distributed teams and creating alignment across locations You communicate clearly and can explain complex technical topics to a range of audiences You are curious about how AI and automation can improve systems and workflows, and apply that thinking pragmatically You care about building inclusive, collaborative environments where teams can grow and do their best work Where You'll Be This role is based in Stockholm or London We offer you the flexibility to work where you work best! There will be some in‑person meetings, but still allows for flexibility to work from home. Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what's playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward‑thinking! So bring us your personal experience, your perspectives, and your background. It's in our differences that we will find the power to keep revolutionizing the way the world listens. At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know — we're here to support you in any way we can. #J-18808-Ljbffr Read Less
  • Remote Senior ML Infrastructure Engineer - Music  

    - East Sussex
    We are seeking a Senior Research Engineer to join our Artist-First AI... Read More
    We are seeking a Senior Research Engineer to join our Artist-First AI Music lab. Our team pioneers and advances state-of-the-art generative technologies for music that create breakthrough experiences for fans and artists. We invent entirely new listening experiences that center and celebrate artists and creatives. All of our products will put artists and songwriters first, through these four principles: Partnerships with record labels, distributors, and music publishers: We’ll develop new products for artists and fans through upfront agreements, not by asking for forgiveness later. Choice in participation: We recognize there’s a wide range of views on use of generative music tools within the artistic community. Therefore, artists and rightsholders will choose if and how to participate to ensure the use of AI tools aligns with the values of the people behind the music. Fair compensation and new revenue: We will build products that create wholly new revenue streams for rightsholders, artists, and songwriters, ensuring they are properly compensated for uses of their work and transparently credited for their contributions. Artist-fan connection : AI tools we develop will not replace human artistry. They will give artists new ways to be creative and connect with fans. We will leverage our role as the place where more than 700 million people already come to listen to music every month to ensure that generative AI deepens artist-fan connections. For more information, see this press release! https://newsroom.spotify.com/2025-10-16/artist-first-ai-music-spotify-collaboration/ What You'll Do Close Collaboration: Work side-by-side with research scientists to conduct ground breaking research in music generation (diffusion, flow matching, or autoregressive models), as well as related domains like ML-based audio processing, music information retrieval, machine learning, and signal processing. Improve model training pipelines. You’ll debug distributed training, optimize data loading at massive scale, and ensure smooth scaling across compute environments. Optimize performance. You’ll profile and accelerate existing training and inference code to make experiments faster and production systems more responsive. Integrate models into production environments. You’ll work directly with platform and product teams to deploy models into the hands of hundreds of millions of Spotify’s users. Incorporate state-of-the-art research. You'll translate models and techniques described in the literature into robust, well-engineered prototypes. Maintain a high-quality codebase. You’ll enforce clear structure, consistency, and testing practices to support long-term maintainability on a codebase shared between members of a fast-paced globally distributed team. Enhance researcher experience. You’ll build internal tooling, libraries, and workflows to make experimentation, debugging, and deployment more efficient for the whole team. Who You Are You have experience training or fine-tuning large machine learning models on GPUs using PyTorch or similar frameworks. You have experience working with cloud platforms like Google Cloud Platform, AWS, or Microsoft Azure. You understand how to debug problems in machine learning training code. You communicate effectively with global teams and are ready to work both face-to-face and asynchronously with collaborators on multiple continents. You have experience optimizing code for performance and can make GPUs “go brrr” (train at maximum efficiency). You learn new concepts and technologies quickly and keep up to date with the rapid pace of development in machine learning and AI. You are resourceful and proactive; when faced with blockers, you seek out solutions through research, experimentation, and collaboration. You’re not afraid to dig deep into the stack: working with lldb, NVIDIA Nsight, or other low-level debugging tools is a plus. You have a solid grasp of computer science concepts like type systems, compilers, parallelism, thread safety, encapsulation, and the like. You have an interest in learning more about audio processing and music information retrieval and you're excited about building amazing products that use these technologies. Where You'll Be We offer you the flexibility to work where you work best! For this role, you can be within the EMEA region as long as we have a work location This team operates within the Central European and GMT time zone for collaboration. Core working hours are CET 3pm-6pm / EST 9am-12pm. Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens. At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can. Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice Read Less
  • Remote Senior ML Infrastructure Engineer - Music  

    - Lancashire
    We are seeking a Senior Research Engineer to join our Artist-First AI... Read More
    We are seeking a Senior Research Engineer to join our Artist-First AI Music lab. Our team pioneers and advances state-of-the-art generative technologies for music that create breakthrough experiences for fans and artists. We invent entirely new listening experiences that center and celebrate artists and creatives. All of our products will put artists and songwriters first, through these four principles: Partnerships with record labels, distributors, and music publishers: We’ll develop new products for artists and fans through upfront agreements, not by asking for forgiveness later. Choice in participation: We recognize there’s a wide range of views on use of generative music tools within the artistic community. Therefore, artists and rightsholders will choose if and how to participate to ensure the use of AI tools aligns with the values of the people behind the music. Fair compensation and new revenue: We will build products that create wholly new revenue streams for rightsholders, artists, and songwriters, ensuring they are properly compensated for uses of their work and transparently credited for their contributions. Artist-fan connection : AI tools we develop will not replace human artistry. They will give artists new ways to be creative and connect with fans. We will leverage our role as the place where more than 700 million people already come to listen to music every month to ensure that generative AI deepens artist-fan connections. For more information, see this press release! https://newsroom.spotify.com/2025-10-16/artist-first-ai-music-spotify-collaboration/ What You'll Do Close Collaboration: Work side-by-side with research scientists to conduct ground breaking research in music generation (diffusion, flow matching, or autoregressive models), as well as related domains like ML-based audio processing, music information retrieval, machine learning, and signal processing. Improve model training pipelines. You’ll debug distributed training, optimize data loading at massive scale, and ensure smooth scaling across compute environments. Optimize performance. You’ll profile and accelerate existing training and inference code to make experiments faster and production systems more responsive. Integrate models into production environments. You’ll work directly with platform and product teams to deploy models into the hands of hundreds of millions of Spotify’s users. Incorporate state-of-the-art research. You'll translate models and techniques described in the literature into robust, well-engineered prototypes. Maintain a high-quality codebase. You’ll enforce clear structure, consistency, and testing practices to support long-term maintainability on a codebase shared between members of a fast-paced globally distributed team. Enhance researcher experience. You’ll build internal tooling, libraries, and workflows to make experimentation, debugging, and deployment more efficient for the whole team. Who You Are You have experience training or fine-tuning large machine learning models on GPUs using PyTorch or similar frameworks. You have experience working with cloud platforms like Google Cloud Platform, AWS, or Microsoft Azure. You understand how to debug problems in machine learning training code. You communicate effectively with global teams and are ready to work both face-to-face and asynchronously with collaborators on multiple continents. You have experience optimizing code for performance and can make GPUs “go brrr” (train at maximum efficiency). You learn new concepts and technologies quickly and keep up to date with the rapid pace of development in machine learning and AI. You are resourceful and proactive; when faced with blockers, you seek out solutions through research, experimentation, and collaboration. You’re not afraid to dig deep into the stack: working with lldb, NVIDIA Nsight, or other low-level debugging tools is a plus. You have a solid grasp of computer science concepts like type systems, compilers, parallelism, thread safety, encapsulation, and the like. You have an interest in learning more about audio processing and music information retrieval and you're excited about building amazing products that use these technologies. Where You'll Be We offer you the flexibility to work where you work best! For this role, you can be within the EMEA region as long as we have a work location This team operates within the Central European and GMT time zone for collaboration. Core working hours are CET 3pm-6pm / EST 9am-12pm. Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens. At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can. Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice Read Less
  • Remote Senior ML Infrastructure Engineer - Music  

    - Bristol City
    We are seeking a Senior Research Engineer to join our Artist-First AI... Read More
    We are seeking a Senior Research Engineer to join our Artist-First AI Music lab. Our team pioneers and advances state-of-the-art generative technologies for music that create breakthrough experiences for fans and artists. We invent entirely new listening experiences that center and celebrate artists and creatives. All of our products will put artists and songwriters first, through these four principles: Partnerships with record labels, distributors, and music publishers: We’ll develop new products for artists and fans through upfront agreements, not by asking for forgiveness later. Choice in participation: We recognize there’s a wide range of views on use of generative music tools within the artistic community. Therefore, artists and rightsholders will choose if and how to participate to ensure the use of AI tools aligns with the values of the people behind the music. Fair compensation and new revenue: We will build products that create wholly new revenue streams for rightsholders, artists, and songwriters, ensuring they are properly compensated for uses of their work and transparently credited for their contributions. Artist-fan connection : AI tools we develop will not replace human artistry. They will give artists new ways to be creative and connect with fans. We will leverage our role as the place where more than 700 million people already come to listen to music every month to ensure that generative AI deepens artist-fan connections. For more information, see this press release! https://newsroom.spotify.com/2025-10-16/artist-first-ai-music-spotify-collaboration/ What You'll Do Close Collaboration: Work side-by-side with research scientists to conduct ground breaking research in music generation (diffusion, flow matching, or autoregressive models), as well as related domains like ML-based audio processing, music information retrieval, machine learning, and signal processing. Improve model training pipelines. You’ll debug distributed training, optimize data loading at massive scale, and ensure smooth scaling across compute environments. Optimize performance. You’ll profile and accelerate existing training and inference code to make experiments faster and production systems more responsive. Integrate models into production environments. You’ll work directly with platform and product teams to deploy models into the hands of hundreds of millions of Spotify’s users. Incorporate state-of-the-art research. You'll translate models and techniques described in the literature into robust, well-engineered prototypes. Maintain a high-quality codebase. You’ll enforce clear structure, consistency, and testing practices to support long-term maintainability on a codebase shared between members of a fast-paced globally distributed team. Enhance researcher experience. You’ll build internal tooling, libraries, and workflows to make experimentation, debugging, and deployment more efficient for the whole team. Who You Are You have experience training or fine-tuning large machine learning models on GPUs using PyTorch or similar frameworks. You have experience working with cloud platforms like Google Cloud Platform, AWS, or Microsoft Azure. You understand how to debug problems in machine learning training code. You communicate effectively with global teams and are ready to work both face-to-face and asynchronously with collaborators on multiple continents. You have experience optimizing code for performance and can make GPUs “go brrr” (train at maximum efficiency). You learn new concepts and technologies quickly and keep up to date with the rapid pace of development in machine learning and AI. You are resourceful and proactive; when faced with blockers, you seek out solutions through research, experimentation, and collaboration. You’re not afraid to dig deep into the stack: working with lldb, NVIDIA Nsight, or other low-level debugging tools is a plus. You have a solid grasp of computer science concepts like type systems, compilers, parallelism, thread safety, encapsulation, and the like. You have an interest in learning more about audio processing and music information retrieval and you're excited about building amazing products that use these technologies. Where You'll Be We offer you the flexibility to work where you work best! For this role, you can be within the EMEA region as long as we have a work location This team operates within the Central European and GMT time zone for collaboration. Core working hours are CET 3pm-6pm / EST 9am-12pm. Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens. At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can. Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice Read Less
  • Remote Senior ML Infrastructure Engineer - Music  

    - Oxfordshire
    We are seeking a Senior Research Engineer to join our Artist-First AI... Read More
    We are seeking a Senior Research Engineer to join our Artist-First AI Music lab. Our team pioneers and advances state-of-the-art generative technologies for music that create breakthrough experiences for fans and artists. We invent entirely new listening experiences that center and celebrate artists and creatives. All of our products will put artists and songwriters first, through these four principles: Partnerships with record labels, distributors, and music publishers: We’ll develop new products for artists and fans through upfront agreements, not by asking for forgiveness later. Choice in participation: We recognize there’s a wide range of views on use of generative music tools within the artistic community. Therefore, artists and rightsholders will choose if and how to participate to ensure the use of AI tools aligns with the values of the people behind the music. Fair compensation and new revenue: We will build products that create wholly new revenue streams for rightsholders, artists, and songwriters, ensuring they are properly compensated for uses of their work and transparently credited for their contributions. Artist-fan connection : AI tools we develop will not replace human artistry. They will give artists new ways to be creative and connect with fans. We will leverage our role as the place where more than 700 million people already come to listen to music every month to ensure that generative AI deepens artist-fan connections. For more information, see this press release! https://newsroom.spotify.com/2025-10-16/artist-first-ai-music-spotify-collaboration/ What You'll Do Close Collaboration: Work side-by-side with research scientists to conduct ground breaking research in music generation (diffusion, flow matching, or autoregressive models), as well as related domains like ML-based audio processing, music information retrieval, machine learning, and signal processing. Improve model training pipelines. You’ll debug distributed training, optimize data loading at massive scale, and ensure smooth scaling across compute environments. Optimize performance. You’ll profile and accelerate existing training and inference code to make experiments faster and production systems more responsive. Integrate models into production environments. You’ll work directly with platform and product teams to deploy models into the hands of hundreds of millions of Spotify’s users. Incorporate state-of-the-art research. You'll translate models and techniques described in the literature into robust, well-engineered prototypes. Maintain a high-quality codebase. You’ll enforce clear structure, consistency, and testing practices to support long-term maintainability on a codebase shared between members of a fast-paced globally distributed team. Enhance researcher experience. You’ll build internal tooling, libraries, and workflows to make experimentation, debugging, and deployment more efficient for the whole team. Who You Are You have experience training or fine-tuning large machine learning models on GPUs using PyTorch or similar frameworks. You have experience working with cloud platforms like Google Cloud Platform, AWS, or Microsoft Azure. You understand how to debug problems in machine learning training code. You communicate effectively with global teams and are ready to work both face-to-face and asynchronously with collaborators on multiple continents. You have experience optimizing code for performance and can make GPUs “go brrr” (train at maximum efficiency). You learn new concepts and technologies quickly and keep up to date with the rapid pace of development in machine learning and AI. You are resourceful and proactive; when faced with blockers, you seek out solutions through research, experimentation, and collaboration. You’re not afraid to dig deep into the stack: working with lldb, NVIDIA Nsight, or other low-level debugging tools is a plus. You have a solid grasp of computer science concepts like type systems, compilers, parallelism, thread safety, encapsulation, and the like. You have an interest in learning more about audio processing and music information retrieval and you're excited about building amazing products that use these technologies. Where You'll Be We offer you the flexibility to work where you work best! For this role, you can be within the EMEA region as long as we have a work location This team operates within the Central European and GMT time zone for collaboration. Core working hours are CET 3pm-6pm / EST 9am-12pm. Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens. At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can. Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice Read Less
  • Remote Senior ML Infrastructure Engineer - Music  

    - Kent
    We are seeking a Senior Research Engineer to join our Artist-First AI... Read More
    We are seeking a Senior Research Engineer to join our Artist-First AI Music lab. Our team pioneers and advances state-of-the-art generative technologies for music that create breakthrough experiences for fans and artists. We invent entirely new listening experiences that center and celebrate artists and creatives. All of our products will put artists and songwriters first, through these four principles: Partnerships with record labels, distributors, and music publishers: We’ll develop new products for artists and fans through upfront agreements, not by asking for forgiveness later. Choice in participation: We recognize there’s a wide range of views on use of generative music tools within the artistic community. Therefore, artists and rightsholders will choose if and how to participate to ensure the use of AI tools aligns with the values of the people behind the music. Fair compensation and new revenue: We will build products that create wholly new revenue streams for rightsholders, artists, and songwriters, ensuring they are properly compensated for uses of their work and transparently credited for their contributions. Artist-fan connection : AI tools we develop will not replace human artistry. They will give artists new ways to be creative and connect with fans. We will leverage our role as the place where more than 700 million people already come to listen to music every month to ensure that generative AI deepens artist-fan connections. For more information, see this press release! https://newsroom.spotify.com/2025-10-16/artist-first-ai-music-spotify-collaboration/ What You'll Do Close Collaboration: Work side-by-side with research scientists to conduct ground breaking research in music generation (diffusion, flow matching, or autoregressive models), as well as related domains like ML-based audio processing, music information retrieval, machine learning, and signal processing. Improve model training pipelines. You’ll debug distributed training, optimize data loading at massive scale, and ensure smooth scaling across compute environments. Optimize performance. You’ll profile and accelerate existing training and inference code to make experiments faster and production systems more responsive. Integrate models into production environments. You’ll work directly with platform and product teams to deploy models into the hands of hundreds of millions of Spotify’s users. Incorporate state-of-the-art research. You'll translate models and techniques described in the literature into robust, well-engineered prototypes. Maintain a high-quality codebase. You’ll enforce clear structure, consistency, and testing practices to support long-term maintainability on a codebase shared between members of a fast-paced globally distributed team. Enhance researcher experience. You’ll build internal tooling, libraries, and workflows to make experimentation, debugging, and deployment more efficient for the whole team. Who You Are You have experience training or fine-tuning large machine learning models on GPUs using PyTorch or similar frameworks. You have experience working with cloud platforms like Google Cloud Platform, AWS, or Microsoft Azure. You understand how to debug problems in machine learning training code. You communicate effectively with global teams and are ready to work both face-to-face and asynchronously with collaborators on multiple continents. You have experience optimizing code for performance and can make GPUs “go brrr” (train at maximum efficiency). You learn new concepts and technologies quickly and keep up to date with the rapid pace of development in machine learning and AI. You are resourceful and proactive; when faced with blockers, you seek out solutions through research, experimentation, and collaboration. You’re not afraid to dig deep into the stack: working with lldb, NVIDIA Nsight, or other low-level debugging tools is a plus. You have a solid grasp of computer science concepts like type systems, compilers, parallelism, thread safety, encapsulation, and the like. You have an interest in learning more about audio processing and music information retrieval and you're excited about building amazing products that use these technologies. Where You'll Be We offer you the flexibility to work where you work best! For this role, you can be within the EMEA region as long as we have a work location This team operates within the Central European and GMT time zone for collaboration. Core working hours are CET 3pm-6pm / EST 9am-12pm. Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens. At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can. Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice Read Less
  • Remote Senior ML Infrastructure Engineer - Music  

    - West Lothian
    We are seeking a Senior Research Engineer to join our Artist-First AI... Read More
    We are seeking a Senior Research Engineer to join our Artist-First AI Music lab. Our team pioneers and advances state-of-the-art generative technologies for music that create breakthrough experiences for fans and artists. We invent entirely new listening experiences that center and celebrate artists and creatives. All of our products will put artists and songwriters first, through these four principles: Partnerships with record labels, distributors, and music publishers: We’ll develop new products for artists and fans through upfront agreements, not by asking for forgiveness later. Choice in participation: We recognize there’s a wide range of views on use of generative music tools within the artistic community. Therefore, artists and rightsholders will choose if and how to participate to ensure the use of AI tools aligns with the values of the people behind the music. Fair compensation and new revenue: We will build products that create wholly new revenue streams for rightsholders, artists, and songwriters, ensuring they are properly compensated for uses of their work and transparently credited for their contributions. Artist-fan connection : AI tools we develop will not replace human artistry. They will give artists new ways to be creative and connect with fans. We will leverage our role as the place where more than 700 million people already come to listen to music every month to ensure that generative AI deepens artist-fan connections. For more information, see this press release! https://newsroom.spotify.com/2025-10-16/artist-first-ai-music-spotify-collaboration/ What You'll Do Close Collaboration: Work side-by-side with research scientists to conduct ground breaking research in music generation (diffusion, flow matching, or autoregressive models), as well as related domains like ML-based audio processing, music information retrieval, machine learning, and signal processing. Improve model training pipelines. You’ll debug distributed training, optimize data loading at massive scale, and ensure smooth scaling across compute environments. Optimize performance. You’ll profile and accelerate existing training and inference code to make experiments faster and production systems more responsive. Integrate models into production environments. You’ll work directly with platform and product teams to deploy models into the hands of hundreds of millions of Spotify’s users. Incorporate state-of-the-art research. You'll translate models and techniques described in the literature into robust, well-engineered prototypes. Maintain a high-quality codebase. You’ll enforce clear structure, consistency, and testing practices to support long-term maintainability on a codebase shared between members of a fast-paced globally distributed team. Enhance researcher experience. You’ll build internal tooling, libraries, and workflows to make experimentation, debugging, and deployment more efficient for the whole team. Who You Are You have experience training or fine-tuning large machine learning models on GPUs using PyTorch or similar frameworks. You have experience working with cloud platforms like Google Cloud Platform, AWS, or Microsoft Azure. You understand how to debug problems in machine learning training code. You communicate effectively with global teams and are ready to work both face-to-face and asynchronously with collaborators on multiple continents. You have experience optimizing code for performance and can make GPUs “go brrr” (train at maximum efficiency). You learn new concepts and technologies quickly and keep up to date with the rapid pace of development in machine learning and AI. You are resourceful and proactive; when faced with blockers, you seek out solutions through research, experimentation, and collaboration. You’re not afraid to dig deep into the stack: working with lldb, NVIDIA Nsight, or other low-level debugging tools is a plus. You have a solid grasp of computer science concepts like type systems, compilers, parallelism, thread safety, encapsulation, and the like. You have an interest in learning more about audio processing and music information retrieval and you're excited about building amazing products that use these technologies. Where You'll Be We offer you the flexibility to work where you work best! For this role, you can be within the EMEA region as long as we have a work location This team operates within the Central European and GMT time zone for collaboration. Core working hours are CET 3pm-6pm / EST 9am-12pm. Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens. At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can. Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice Read Less
  • Remote Senior ML Infrastructure Engineer - Music  

    - Warrington
    We are seeking a Senior Research Engineer to join our Artist-First AI... Read More
    We are seeking a Senior Research Engineer to join our Artist-First AI Music lab. Our team pioneers and advances state-of-the-art generative technologies for music that create breakthrough experiences for fans and artists. We invent entirely new listening experiences that center and celebrate artists and creatives. All of our products will put artists and songwriters first, through these four principles: Partnerships with record labels, distributors, and music publishers: We’ll develop new products for artists and fans through upfront agreements, not by asking for forgiveness later. Choice in participation: We recognize there’s a wide range of views on use of generative music tools within the artistic community. Therefore, artists and rightsholders will choose if and how to participate to ensure the use of AI tools aligns with the values of the people behind the music. Fair compensation and new revenue: We will build products that create wholly new revenue streams for rightsholders, artists, and songwriters, ensuring they are properly compensated for uses of their work and transparently credited for their contributions. Artist-fan connection : AI tools we develop will not replace human artistry. They will give artists new ways to be creative and connect with fans. We will leverage our role as the place where more than 700 million people already come to listen to music every month to ensure that generative AI deepens artist-fan connections. For more information, see this press release! https://newsroom.spotify.com/2025-10-16/artist-first-ai-music-spotify-collaboration/ What You'll Do Close Collaboration: Work side-by-side with research scientists to conduct ground breaking research in music generation (diffusion, flow matching, or autoregressive models), as well as related domains like ML-based audio processing, music information retrieval, machine learning, and signal processing. Improve model training pipelines. You’ll debug distributed training, optimize data loading at massive scale, and ensure smooth scaling across compute environments. Optimize performance. You’ll profile and accelerate existing training and inference code to make experiments faster and production systems more responsive. Integrate models into production environments. You’ll work directly with platform and product teams to deploy models into the hands of hundreds of millions of Spotify’s users. Incorporate state-of-the-art research. You'll translate models and techniques described in the literature into robust, well-engineered prototypes. Maintain a high-quality codebase. You’ll enforce clear structure, consistency, and testing practices to support long-term maintainability on a codebase shared between members of a fast-paced globally distributed team. Enhance researcher experience. You’ll build internal tooling, libraries, and workflows to make experimentation, debugging, and deployment more efficient for the whole team. Who You Are You have experience training or fine-tuning large machine learning models on GPUs using PyTorch or similar frameworks. You have experience working with cloud platforms like Google Cloud Platform, AWS, or Microsoft Azure. You understand how to debug problems in machine learning training code. You communicate effectively with global teams and are ready to work both face-to-face and asynchronously with collaborators on multiple continents. You have experience optimizing code for performance and can make GPUs “go brrr” (train at maximum efficiency). You learn new concepts and technologies quickly and keep up to date with the rapid pace of development in machine learning and AI. You are resourceful and proactive; when faced with blockers, you seek out solutions through research, experimentation, and collaboration. You’re not afraid to dig deep into the stack: working with lldb, NVIDIA Nsight, or other low-level debugging tools is a plus. You have a solid grasp of computer science concepts like type systems, compilers, parallelism, thread safety, encapsulation, and the like. You have an interest in learning more about audio processing and music information retrieval and you're excited about building amazing products that use these technologies. Where You'll Be We offer you the flexibility to work where you work best! For this role, you can be within the EMEA region as long as we have a work location This team operates within the Central European and GMT time zone for collaboration. Core working hours are CET 3pm-6pm / EST 9am-12pm. Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens. At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can. Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice Read Less
  • Remote Senior ML Infrastructure Engineer - Music  

    - Greater Manchester
    We are seeking a Senior Research Engineer to join our Artist-First AI... Read More
    We are seeking a Senior Research Engineer to join our Artist-First AI Music lab. Our team pioneers and advances state-of-the-art generative technologies for music that create breakthrough experiences for fans and artists. We invent entirely new listening experiences that center and celebrate artists and creatives. All of our products will put artists and songwriters first, through these four principles: Partnerships with record labels, distributors, and music publishers: We’ll develop new products for artists and fans through upfront agreements, not by asking for forgiveness later. Choice in participation: We recognize there’s a wide range of views on use of generative music tools within the artistic community. Therefore, artists and rightsholders will choose if and how to participate to ensure the use of AI tools aligns with the values of the people behind the music. Fair compensation and new revenue: We will build products that create wholly new revenue streams for rightsholders, artists, and songwriters, ensuring they are properly compensated for uses of their work and transparently credited for their contributions. Artist-fan connection : AI tools we develop will not replace human artistry. They will give artists new ways to be creative and connect with fans. We will leverage our role as the place where more than 700 million people already come to listen to music every month to ensure that generative AI deepens artist-fan connections. For more information, see this press release! https://newsroom.spotify.com/2025-10-16/artist-first-ai-music-spotify-collaboration/ What You'll Do Close Collaboration: Work side-by-side with research scientists to conduct ground breaking research in music generation (diffusion, flow matching, or autoregressive models), as well as related domains like ML-based audio processing, music information retrieval, machine learning, and signal processing. Improve model training pipelines. You’ll debug distributed training, optimize data loading at massive scale, and ensure smooth scaling across compute environments. Optimize performance. You’ll profile and accelerate existing training and inference code to make experiments faster and production systems more responsive. Integrate models into production environments. You’ll work directly with platform and product teams to deploy models into the hands of hundreds of millions of Spotify’s users. Incorporate state-of-the-art research. You'll translate models and techniques described in the literature into robust, well-engineered prototypes. Maintain a high-quality codebase. You’ll enforce clear structure, consistency, and testing practices to support long-term maintainability on a codebase shared between members of a fast-paced globally distributed team. Enhance researcher experience. You’ll build internal tooling, libraries, and workflows to make experimentation, debugging, and deployment more efficient for the whole team. Who You Are You have experience training or fine-tuning large machine learning models on GPUs using PyTorch or similar frameworks. You have experience working with cloud platforms like Google Cloud Platform, AWS, or Microsoft Azure. You understand how to debug problems in machine learning training code. You communicate effectively with global teams and are ready to work both face-to-face and asynchronously with collaborators on multiple continents. You have experience optimizing code for performance and can make GPUs “go brrr” (train at maximum efficiency). You learn new concepts and technologies quickly and keep up to date with the rapid pace of development in machine learning and AI. You are resourceful and proactive; when faced with blockers, you seek out solutions through research, experimentation, and collaboration. You’re not afraid to dig deep into the stack: working with lldb, NVIDIA Nsight, or other low-level debugging tools is a plus. You have a solid grasp of computer science concepts like type systems, compilers, parallelism, thread safety, encapsulation, and the like. You have an interest in learning more about audio processing and music information retrieval and you're excited about building amazing products that use these technologies. Where You'll Be We offer you the flexibility to work where you work best! For this role, you can be within the EMEA region as long as we have a work location This team operates within the Central European and GMT time zone for collaboration. Core working hours are CET 3pm-6pm / EST 9am-12pm. Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens. At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can. Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice Read Less

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