Senior / AI Scientist (Reinforcement Learning)

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    "description": "<p><span style=\"font-size: 12pt\">Resaro was founded on the belief that AI will change the world in ways we cannot even imagine, but every new technology needs safeguards to advance.</span></p>\n<p><br></p>\n<p><span style=\"color: rgb(67, 67, 67); font-family: Arial, sans-serif; font-size: 12pt\">About the Role</span></p>\n<p>We are looking for an AI Scientist with a deep foundation in Machine Learning and a passion for the</p>\n<p>frontiers of Reinforcement Learning. You will be responsible for building a robust framework to stress-test and audit Reinforcement Learning systems, making sure they are fit for purpose and safe to be deployed. We value strong technical ability and real world experience and there will be room to solve challenging problems and adopt cutting edge technology into business applications.</p>\n<p><br></p>\n<p>YOU WILL</p>\n<ul>\n<li><span style=\"font-weight: bold\">Implement Reinforcement Learning Evaluation</span>: Execute a dedicated work plan to build frameworks that evaluate the performance, safety, and alignment of RL agents.</li>\n<li><span style=\"font-weight: bold\">Build Uncertainty-Aware Tools</span>: Use Bayesian ML models (GPs, BNNs) to create metrics for model confidence and risk.</li>\n<li><span style=\"font-weight: bold\">Develop Testing Infrastructure:</span> Design and set up the debugging and automated testing frameworks required to evaluate non-deterministic systems.</li>\n<li><span style=\"font-weight: bold\">Execute Technical Evaluations</span>: Perform \"red-team\" tests and benchmarks on models usingTrust Region methods (PPO) and RL from Human Feedback (RLHF).</li>\n<li><span style=\"font-weight: bold\">Master the RL Stack</span>: Work across the entire stack, from environment interfacing to policy optimization, with the opportunity to grow into Multi-Agent RL (MARL) technologies.</li>\n</ul>\n<p><br></p>\n<p>YOU ARE ABLE TO</p>\n<ul>\n<li><span style=\"font-weight: bold\">Execute with Precision</span>: Take high-level theoretical designs and turn them into clean, production-ready code.</li>\n<li><span style=\"font-weight: bold\">Think from First Principles</span>: Use your technical background to solve challenging problems from the ground up.</li>\n<li><span style=\"font-weight: bold\">Collaborate &amp; Learn</span>: Work effectively under senior mentorship to adopt new research into business applications.</li>\n<li><span style=\"font-weight: bold\">Navigate Uncertainty</span>: Thrive in a fast-paced environment where the mission of AI safety is paramount.</li>\n</ul>\n<p><br></p>\n<p>YOU HAVE</p>\n<ul>\n<li><span style=\"font-weight: bold\">Mastery of the ML Stack</span>: Strong proficiency in Python, NumPy, and PyTorch.</li>\n<li><span style=\"font-weight: bold\">Theoretical Foundation</span>: A background in ML theory, Mathematics, or Physics.</li>\n<li><span style=\"font-weight: bold\">Bayesian Knowledge</span>: Experience with Bayesian ML models (e.g., Gaussian Processes, Bayesian Neural Networks).</li>\n<li><span style=\"font-weight: bold\">RL Specialization</span>: Practical experience or familiarity with Trust Region methods (PPO) and RL from Human Feedback (RLHF).</li>\n<li><span style=\"font-weight: bold\">Engineering Rigor</span>: Proven ability in debugging and setting up automated testing frameworks.</li>\n</ul>\n<p><br></p>\n<p><br>NICE TO HAVE</p>\n<ul>\n<li>Knowledge of Multi-Agent RL (MARL) technology.</li>\n<li>Interest in applied research on the safe and responsible use of AI.</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-size: 12pt\">ABOUT US</span></p>\n<p><span style=\"font-size: 12pt\">Resaro is a global AI Assurance company, pioneering the field of AI testing and evaluation. We are a team of AI experts, engineers, and data scientists. Our mission is to ensure an AI market worthy of trust.</span></p>\n<p><br></p>\n<p><span style=\"font-size: 12pt\">Resaro is an Equal Opportunity Employer. We respect each individual and support the diverse cultures, perspectives, skills and experiences within our teams.</span></p>",
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