Ekarobotics
Machine Learning / Reinforcement Learning Engineer
Boston Area
Sponsorship not specifiedDetected 501 days ago
PythonAlgorithmsMachine LearningDeep LearningPyTorchNLPRoboticsResearchCollaborationPipeline Integrity
About the role
- Our approach, grounded in physics, unlocks superhuman capabilities.
- Our team consists of pioneers in robotics and machine learning.
Responsibilities
- 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
- identify bottlenecks and implement improvements in collaboration with the robotics team.
- Simulation: Design simulation models and domain randomization strategies; collaborate with the robotics team to ensure alignment with physical systems.
- 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.
- 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.
Requirements
- Robotics Toolkit: Experience with physics engines (e.g., Isaac Sim, MuJoCo, PyBullet) and robotics middleware (ROS/ROS2).
- Experience with physics engines (e.g., Isaac Sim, MuJoCo, PyBullet) and robotics middleware (ROS/ROS2).
- 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.
- 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.
Benefits
- Algorithm Development: Research and implement reinforcement learning and supervised learning algorithms for robotic manipulation.
Company info
- Eka Robotics is on a mission to build intelligence for the physical world - robots that are fast, general, and reliable.
- We are defining the frontier of robotics research and deployment.
- 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.
Apply directly at Ekarobotics →Create a free account for alerts like thisView Ekarobotics immigration profile
This listing is sourced directly from Ekarobotics's careers page and normalized into a canonical job model.