Machine Learning / Reinforcement Learning Infrastructure Engineer

The role

You will design, implement, and maintain large-scale model training systems. You will build developer tooling and scale reinforcement learning and machine learning pipelines across compute clusters.

What you will do

• Design, implement, and maintain systems for large-scale model training.
• Build abstractions for launching, monitoring, debugging, and reproducing experiments.
• Scale reinforcement learning and machine learning pipelines across compute clusters.
• Ensure efficient allocation and utilization of cloud-based compute resources.
• Partner with the research team to build infrastructure for cutting-edge methods.
• Contribute to core JAX model and training code.

Required qualifications

• 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, 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.
• Deep ownership mindset.
• Passion for building tools that improve the developer experience.
• Experience building automated testing pipelines, CI/CD for ML workflows, and custom logging/telemetry stacks.

Nice to have

• Hands-on experience with large-scale training using JAX
• Background in robotics, reinforcement learning or other machine learning systems.
• Experience designing abstractions that balance researcher flexibility with system reliability.

About the company

Eka Robotics is on a mission to build intelligence for the physical world - robots that are fast, general, and reliable. Their team consists of pioneers in robotics and machine learning.