onsite
Machine Learning Engineer - Bespoke Labs
ML Engineer
Machine Learning Engineer focused on designing and deploying reinforcement learning environments and tasks, leveraging Python, PyTorch, and OpenAI Gym to push agent performance in digital worlds.
About the role
Key Responsibilities
- Collaborate with research scientists to design, implement, and iterate on RL environments and tasks that scale to complex digital worlds.
- Develop high‑performance simulation pipelines using Python and PyTorch, ensuring reproducibility and efficient GPU utilization.
- Integrate data pipelines for large‑scale reasoning datasets, performing data curation, preprocessing, and annotation management.
- Deploy models and environments to cloud infrastructure (AWS) for continuous training and evaluation.
- Document environment specifications, benchmark results, and best practices for internal and external stakeholders.
Requirements
- Strong programming skills in Python with experience in deep learning frameworks (PyTorch/TensorFlow).
- Hands‑on experience designing and implementing reinforcement learning environments (OpenAI Gym, Unity ML‑Agents, or similar).
- Solid understanding of RL algorithms (DQN, PPO, SAC, etc.) and ability to experiment with novel approaches.
- Experience with large‑scale data engineering, including data ingestion, cleaning, and storage on cloud platforms.
- Excellent communication skills and a collaborative mindset to work across research and engineering teams.
Skills
pythonpytorchreinforcement learning