{"id":779951,"url":"https://alion.io/job/ekarobotics-machine-learning-reinforcement-learning-engineer","title":"Machine Learning / Reinforcement Learning Engineer","company":{"id":674021,"name":"EKA Robotics","domain":"ekarobotics.com","url":"https://alion.io/company/ekarobotics","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"C","score":67,"open_postings":11,"ghost_share":0.545,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-29T05:49:05Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Boston, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":137000,"max_usd":305000,"period":"year","method":"role_country_seniority_unknown","sample_n":4425},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Isaac Sim","optional":false},{"name":"JAX","optional":false},{"name":"Machine Learning","optional":false},{"name":"MuJoCo","optional":false},{"name":"PyBullet","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"ROS","optional":false},{"name":"ROS2","optional":false},{"name":"Sim-to-Real","optional":false},{"name":"Synthetic Data","optional":false},{"name":"Transformers","optional":false}],"status":"live","first_seen_at":"2025-03-08T02:34:40Z","employer_posted_date":"2025-03-08","last_verified_at":"2026-10-29T23:46:27Z","board_verified":true,"closed_at":null,"days_open":600,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":600},"description":"Eka Robotics\nEka 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.\nOur 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.\nResponsibilities\nAlgorithm Development: Research and implement reinforcement learning and supervised learning algorithms for robotic manipulation.\n\nSimulation: Design simulation models and domain randomization strategies; collaborate with the robotics team to ensure alignment with physical systems.\n\nPerformance Optimization: Design experiments to evaluate and optimize model architectures for sample complexity and policy performance with real-time execution constraints.\n\nData & Pipeline Engineering: Develop scalable data management pipelines for real and synthetic data; evaluate and select algorithms that maximize data efficiency and overall policy performance.\n\nOn-Robot Evaluation: Deploy, evaluate, and debug policies on physical hardware; identify bottlenecks and implement improvements in collaboration with the robotics team.\n\nQualifications\nEducation: BS, MS, or PhD in Computer Science, Robotics, or a related field.\n\nCore Expertise: Deep theoretical and practical knowledge of reinforcement learning and supervised learning algorithms.\n\nRobotics Toolkit: Experience with physics engines (e.g., Isaac Sim, MuJoCo, PyBullet) and robotics middleware (ROS/ROS2).\n\nArchitectural Depth: A deep understanding of modern architectures, including Transformers, CNNs, and Foundation Models.\n\nTechnical Proficiency: Expert-level Python skills and proficiency in deep learning frameworks such as PyTorch or JAX.\n\nEngineering Rigor: A strong commitment to clean code, version control, and reproducible experimental workflows.\n\nTrack 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 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