Machine Learning / Reinforcement Learning Engineer

Eka • Cambridge, MA

2d

About The Position

Eka Robotics is on a mission to build intelligence for the physical world - robots that are fast, general, and reliable. Our approach, grounded in physics, unlocks superhuman capabilities. We are defining the frontier of robotics research and deployment. Our team consists of pioneers in robotics and machine learning. We are now hiring to scale our R&D effort. We are looking for hands-on individuals who are excited to help shape the future of robotics.

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 (e.g., Isaac Sim, MuJoCo, PyBullet) and robotics middleware (ROS/ROS2).
• A deep understanding of modern architectures, including Transformers, CNNs, and Foundation Models.
• Expert-level Python skills and proficiency in deep learning frameworks such as PyTorch or JAX.
• A strong commitment to clean code, version control, and reproducible experimental workflows.
• 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.

Responsibilities

• Research and implement reinforcement learning and supervised learning algorithms for robotic manipulation.
• Design simulation models and domain randomization strategies; collaborate with the robotics team to ensure alignment with physical systems.
• Design experiments to evaluate and optimize model architectures for sample complexity and policy performance with real-time execution constraints.
• Develop scalable data management pipelines for real and synthetic data; evaluate and select algorithms that maximize data efficiency and overall policy performance.
• Deploy, evaluate, and debug policies on physical hardware; identify bottlenecks and implement improvements in collaboration with the robotics team.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior