over 1 year ago
Boston, MA, USASenior
Responsibilities
- Research and implement reinforcement learning and supervised learning algorithms for robotic manipulation.
- Design simulation models and domain randomization strategies aligned with physical robotic systems.
- Evaluate and optimize model architectures for sample complexity and policy performance under real-time execution constraints.
- Develop scalable data management pipelines for real and synthetic data.
- Deploy, evaluate, and debug learned policies on physical hardware and improve performance with the robotics team.
Requirements
- BS, MS, or PhD in Computer Science, Robotics, or a related field.
- Deep theoretical and practical knowledge of reinforcement learning and supervised learning algorithms.
- Experience with physics engines such as Isaac Sim, MuJoCo, or PyBullet and robotics middleware such as ROS or ROS2.
- Deep understanding of Transformers, CNNs, and Foundation Models.
- Expert-level Python skills and proficiency with PyTorch or JAX.
- Commitment to clean code, version control, and reproducible experimental workflows.
- Publications in top-tier robotics or machine learning conferences, or a practical project portfolio demonstrating strong expertise.
Categories
ML EngineeringRobotics
About Eka
Eka Robotics develops general-purpose robotic systems and autonomy software to bring reliable, high‑speed automation to real‑world environments. The company applies physics‑based methods alongside modern AI to build and deploy robots that can handle varied tasks across industries. Privately held and based in Cambridge, Massachusetts, it focuses on advancing and commercializing robotic intelligence for practical deployment.