Job Summary:
Eka Robotics is on a mission to build intelligence for the physical world through advanced robotics. They are seeking a Reinforcement/Machine Learning Infrastructure Engineer to design, implement, and maintain large-scale model training systems that will enhance their robotics research and deployment efforts.
Responsibilities:
• Own Training Infrastructure: Design, implement, and maintain robust systems for large-scale model training, including job orchestration, scheduling, checkpointing, and experiment tracking.
• Developer Experience & Tooling: Build streamlined, intuitive abstractions for launching, monitoring, debugging, and reproducing experiments, minimizing friction and maximizing productivity for our research teams.
• Scale Distributed Training: Work closely with researchers to reliably scale reinforcement learning and machine learning pipelines across compute clusters.
• Resource Management: Ensure efficient allocation and utilization of cloud-based compute resources while building the foundational systems needed for future scaling.
• Collaborate with Researchers: Partner with the research team to understand their needs, build infrastructure that supports cutting-edge methods, guide best practices for training at scale, and contribute to core JAX model and training code.
Qualifications:
Required:
• BS, MS or higher in Computer Science, Computer Engineering, Machine Learning or a related technical field.
• Strong software engineering fundamentals with a proven track record of building ML training infrastructure, internal developer platforms, or scalable systems.
• Hands-on experience with large-scale training using JAX (preferred), PyTorch, or TensorFlow.
• Familiarity with distributed training, multi-host setups, data pipelines, and managing workloads on cloud platforms or orchestration systems (e.g., Kubernetes, SLURM, GCP, AWS).
• Strong cross-functional communication skills, a deep ownership mindset, and a passion for building tools that improve the developer experience.
• Experience building automated testing pipelines, CI/CD for ML workflows, and custom logging/telemetry stacks.
Preferred:
• Background in robotics, reinforcement learning or other machine learning systems.
• Experience designing abstractions that balance researcher flexibility with system reliability.
Company:
Founded in , the company is headquartered in Cambridge, MA, US, , with a team of 11-50 employees. The company is currently Early Stage.