Hybrid AI Scientist – Reinforcement Learning

Posted last month

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About the role

  • AI Scientist focusing on Reinforcement Learning at Resaro, an AI Assurance company. Building frameworks for evaluating and auditing AI systems and ensuring deployment safety.

Responsibilities

  • Execute a dedicated work plan to build frameworks that evaluate the performance, safety, and alignment of RL agents
  • Use Bayesian ML models (GPs, BNNs) to create metrics for model confidence and risk
  • Design and set up the debugging and automated testing frameworks required to evaluate non-deterministic systems
  • Perform "red-team" tests and benchmarks on models using Trust Region methods (PPO) and RL from Human Feedback (RLHF)
  • Work across the entire stack, from environment interfacing to policy optimization, with the opportunity to grow into Multi-Agent RL (MARL) technologies

Requirements

  • Strong proficiency in Python, NumPy, and PyTorch
  • A background in ML theory, Mathematics, or Physics
  • Experience with Bayesian ML models (e.g., Gaussian Processes, Bayesian Neural Networks)
  • Practical experience or familiarity with Trust Region methods (PPO) and RL from Human Feedback (RLHF)
  • Proven ability in debugging and setting up automated testing frameworks.

Benefits

  • Hybrid work arrangement
  • Professional development opportunities

Job title

AI Scientist – Reinforcement Learning

Job type

Experience level

Junior

Salary

Not specified

Degree requirement

Bachelor's Degree

Location requirements

HybridSingapore

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