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Mosaic People Solutions on Behalf of Client

About the Opportunity A venture-backed medical device company is developing a novel therapy platform for treating complex cardiac disorders.The company has demonstrated promising early results and is now advancing toward a clinically deployable system. This is a rare opportunity to join a highly technical, mission-driven team working at the intersection of machine learning, control systems, and human physiology.Role OverviewThis role will lead the development of an adaptive, reinforcement learning&ndash;based control system within a dynamic and partially observable biological environment.You will work on a complex sequential decision-making problem, where the system must interpret high-dimensional physiological signals, predict outcomes of interventions, and continuously optimize performance in real time.The role includes both simulation-based development and collaboration with experimental teams to translate algorithms into real-world applications.Key Responsibilities<ul><li>Design and implement reinforcement learning algorithms for adaptive control</li><li>Develop state representations and reward functions for complex physiological systems</li><li>Build and evaluate model-based, offline, or constrained RL approaches</li><li>Utilize simulation environments to train, test, and validate algorithms</li><li>Develop signal processing pipelines for time-series physiological data</li><li>Apply control theory principles to ensure system stability and safety</li><li>Partner cross-functionally with engineering and research teams to support system development and validation</li></ul>Required Qualifications<ul><li>MS or PhD in Electrical Engineering, Computer Science, Biomedical Engineering, or related field</li><li>Strong expertise in reinforcement learning and/or control systems</li><li>Experience with Python (e.g., PyTorch, TensorFlow)</li><li>Background in signal processing and time-series analysis</li><li>Experience working with complex, dynamic systems</li></ul>Preferred Qualifications<ul><li>Experience applying ML/RL to physical or safety-critical systems (e.g., robotics, autonomous systems)</li><li>Exposure to healthcare, medical devices, or physiological data</li><li>Familiarity with optimization methods (e.g., Bayesian optimization, evolutionary algorithms)</li><li>Understanding of system validation, robustness, and safety considerations</li></ul>Pay: From $100,000.00 per yearBenefits:<ul><li>Health insurance</li></ul>Work Location: In person

AI / Reinforcement Learning Engineer

Join Mosaic People Solutions on Behalf of Client and explore 1   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Mosaic People Solutions on Behalf of Client

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AI / Reinforcement Learning Engineer