Reinforcement Learning Engineer
New
Fully remote position within the United States.Full-TimeSenior
Salary100,000 - 150,000 USD per year
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Job Details
- Experience
- 6+ years
- Required Skills
- PythonMachine LearningPyTorchTensorflowDeep LearningDistributed Systems
Requirements
- Master’s or PhD in Computer Science, Machine Learning, or equivalent.
- 6+ years of experience in reinforcement learning research and engineering.
- Strong Python programming skills.
- Experience with PyTorch or TensorFlow.
- Hands-on experience with RL libraries or custom RL training stacks.
- Understanding of probability, optimization, and reinforcement learning theory.
- Experience designing reward functions in complex environments.
- Familiarity with simulation environments and large-scale training pipelines.
- Experience training neural policies on GPU-based distributed systems.
- Strong debugging and analytical skills.
Responsibilities
- Design and implement reinforcement learning systems for sequential decision-making problems.
- Develop and maintain high-fidelity simulation environments.
- Implement and evaluate RL algorithms including policy gradient, actor-critic, and offline methods.
- Engineer reward functions that align model behavior with business objectives.
- Utilize RLHF and DPO for fine-tuning large-scale models.
- Build distributed training infrastructure and scalable data pipelines.
- Design rigorous evaluation frameworks and safety mechanisms.
- Monitor production models for drift and performance degradation.
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