Machine Learning Engineer – RL
Tasks
- Apply offline reinforcement learning and imitation learning
- Build distributed reinforcement learning training infrastructure
- Design evaluation protocols with out of distribution and adversarial tests
- Design reinforcement learning solutions for sequential decision making
- Develop simulation environments for agent training
- Document methodology design decisions and operational characteristics
- Engineer reward functions and shaping strategies
- Implement and evaluate reinforcement learning algorithms
- Implement safety mechanisms and constraint enforcement
- Monitor deployed policies for drift and regression
- Optimize training stability and sample efficiency
- Translate reinforcement learning research into production solutions
- Use RLHF and DPO for large language model fine tuning
Perks/Benefits
- N/A
Skills/Tech-stack
Actor-critic | Adversarial Testing | Constraint Enforcement | DPO | Deep learning | Distributed Training | Distribution testing | Drift Detection | Experience Replay | GPU Computing | Human-in-the-loop | Imitation Learning | Language Models | Large Language Models | Off Policy | Off Policy Learning | Offline Reinforcement Learning | Out of Distribution | Out of Distribution Testing | Policy Gradient | Policy learning | Python | RLHF | Reinforcement Learning | Reward shaping | Simulation Environments | The Loop
Education
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