Job Description Machine Learning Research Engineer
Company:** Blue Prism Limited
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Job Summary
Blue Prism is seeking a talented Machine Learning Research Engineer to join our innovative R&D team. In this role, you will be instrumental in researching, designing, and implementing cutting-edge machine learning algorithms and models to enhance our intelligent automation platform, driving the future of enterprise-grade AI.
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Job Responsibilities
* Conduct research into novel machine learning algorithms, deep learning architectures, and statistical models relevant to intelligent automation, natural language processing, computer vision, and predictive analytics.
* Design, develop, and implement robust and scalable machine learning models and pipelines, from data ingestion and feature engineering to model training, evaluation, and deployment.
* Collaborate with product managers and other engineering teams to translate research findings into production-ready features and components for Blue Prism's platform.
* Evaluate the performance of machine learning models, analyze results, and iteratively refine models for improved accuracy, efficiency, and real-world applicability.
* Stay abreast of the latest advancements in machine learning research and industry best practices, actively contributing to the company's knowledge base and innovation strategy.
* Participate in code reviews, contribute to technical documentation, and mentor junior engineers on machine learning principles and techniques.
* Experiment with and develop solutions for challenging problems in areas such as anomaly detection, process mining, intelligent document processing, and human-in-the-loop AI.
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Job Qualifications
* PhD or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a closely related quantitative field.
* Proven experience (3+ years) in a machine learning research or engineering role, with a strong portfolio of projects demonstrating practical application of ML techniques.
* Expertise in programming languages such as Python, with proficiency in relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn, Pandas, NumPy).
* Solid understanding of machine learning fundamentals, including supervised/unsupervised learning, reinforcement learning, deep learning, and statistical modeling.
* Experience with cloud platforms (e.g., Azure, AWS, GCP) and MLOps practices for deploying and managing ML models in production.
* Familiarity with data processing and big data technologies (e.g., Spark, Hadoop) is a plus.
* Strong problem-solving skills, analytical thinking, and the ability to conduct independent research.
* Excellent communication skills, both written and verbal, with the ability to articulate complex technical concepts to diverse audiences.
* Ability to work effectively in a collaborative, fast-paced, and agile environment.
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