Machine Learning / Reinforcement Learning EngineerEka • Cambridge, Massachusetts, United States
Machine Learning / Reinforcement Learning Engineer
Eka
- Cambridge, Massachusetts, United States
- Cambridge, Massachusetts, United States
Über
Responsibilities Algorithm Development:
Research and implement reinforcement learning and supervised learning algorithms for robotic manipulation.
Simulation:
Design simulation models and domain randomization strategies; collaborate with the robotics team to ensure alignment with physical systems.
Performance Optimization:
Design experiments to evaluate and optimize model architectures for sample complexity and policy performance with real-time execution constraints.
Data & Pipeline Engineering:
Develop scalable data management pipelines for real and synthetic data; evaluate and select algorithms that maximize data efficiency and overall policy performance.
On-Robot Evaluation:
Deploy, evaluate, and debug policies on physical hardware; identify bottlenecks and implement improvements in collaboration with the robotics team.
Qualifications Education:
BS, MS, or PhD in Computer Science, Robotics, or a related field.
Core Expertise:
Deep theoretical and practical knowledge of reinforcement learning and supervised learning algorithms.
Robotics Toolkit:
Experience with physics engines (e.g., Isaac Sim, MuJoCo, PyBullet) and robotics middleware (ROS/ROS2).
Architectural Depth:
A deep understanding of modern architectures, including Transformers, CNNs, and Foundation Models.
Technical Proficiency:
Expert-level Python skills and proficiency in deep learning frameworks such as PyTorch or JAX.
Engineering Rigor:
A strong commitment to clean code, version control, and reproducible experimental workflows.
Track Record:
A history of publications in top-tier robotics or machine learning conferences, or a portfolio of projects providing strong practical evidence of expertise in the field.
Sprachkenntnisse
- English
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