--- title: 'Machine Learning / Reinforcement Learning Infrastructure Engineer at Eka' canonical: 'https://feeny.ai/job/machine-learning-reinforcement-learning-infrastructure-engineer-eka-boston-czmmjx0d7nk3' type: 'job' last_seen: '2026-09-08' --- # Machine Learning / Reinforcement Learning Infrastructure Engineer at Eka - **Company:** Eka - **Location:** Boston, MA - **Employment:** full-time - **Work type:** onsite - **Posted:** 2025-03-08 - **Last confirmed live:** 2026-09-08 - **Apply:** https://jobs.ashbyhq.com/ekarobotics/c7039cd4-4471-4eb8-8a1f-4dc05bbc7cbf ## Job description Eka Robotics 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. ## The Role We are looking for a Reinforcement/Machine Learning Infrastructure Engineer to shape our training infrastructure. In this role, you will be responsible for designing, implementing, and maintaining the large-scale model training systems that power our next generation of robot learning. We believe that world-class infrastructure is the foundation for moving research into production. You will focus on building an exceptional developer experience, creating intuitive and efficient tooling that our engineers and scientists love to use. Your work will directly accelerate our research cycles, making it effortless to test new ideas and scale successful experiments into production training runs. You will work closely with researchers to ensure our infrastructure scales seamlessly from prototyping to large-scale distributed training. This is a hands-on, high-impact role at the intersection of machine learning, software engineering, and scalable infrastructure. ## 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. ## Minimum Qualifications - Education: BS, MS or higher in Computer Science, Computer Engineering, Machine Learning or a related technical field. - Software Engineering: Strong software engineering fundamentals with a proven track record of building ML training infrastructure, internal developer platforms, or scalable systems. - Deep Learning Frameworks: Hands-on experience with large-scale training using JAX (preferred), PyTorch, or TensorFlow. - Distributed Systems: Familiarity with distributed training, multi-host setups, data pipelines, and managing workloads on cloud platforms or orchestration systems (e.g., Kubernetes, SLURM, GCP, AWS). - Communication & Ownership: Strong cross-functional communication skills, a deep ownership mindset, and a passion for building tools that improve the developer experience. - Infrastructure & DevOps: Experience building automated testing pipelines, CI/CD for ML workflows, and custom logging/telemetry stacks. ## Preferred Qualifications - Domain Experience: Background in robotics, reinforcement learning or other machine learning systems. - Systems Design: Experience designing abstractions that balance researcher flexibility with system reliability. ## About Eka ## Company Overview - **One-liner**: Eka Robotics is building general-purpose, dexterous robots that master physics through self-supervised learning and a novel Vision-Force-Action (VFA) model, aiming to deploy safe, collaborative intelligence into the physical world. - **Entity Type**: Private (Startup, Pre-Seed / Angel-backed) - **Headquarters**: Cambridge, Massachusetts, United States - **Founded**: 2025 - **Founders**: Pulkit Agrawal and Tuomas Haarnoja ## Core Business - **Primary industry/industries**: Robotics Engineering, Artificial Intelligence, Hardware, Automation - **Target customers**: B2B, Enterprise (logistics, manufacturing, material handling) - **Mission or purpose statement**: To build intelligence for the physical world in its native language: force, creating robots that master physics, collaborate safely with humans, and generalize across objects, tasks, and environments. ## Products & Services - **Vision-Force-Action (VFA) Model**: A new AI foundation model that unites generality, performance, and safety. It allows robots to perceive the world visually, interact with it through force (the "native language" of physics), and execute actions. This model is designed to overcome the traditional trade-off between generality and performance in robotics. - **Dexterous Robotic Manipulation Platform**: A hardware and software platform for dexterous, collaborative robots. The platform is designed to be safe around humans, environment-agnostic, and capable of mastering the unexpected through a single model that generalizes across objects, tasks, and environments. ## Market Standing - **Valuation/Market Cap**: Not publicly available (Pre-Seed / Angel-backed startup). - **Key Metric**: Total Funding: Not publicly available (described as "angel-backed" with no known external funding rounds disclosed). - **Notable Investors/Partners**: Angel-backed; specific investors not publicly disclosed. The founding team has deep ties to MIT, Berkeley, Harvard, DeepMind, Microsoft, and Boston Dynamics. - **Growth Signals**: Extremely early stage (founded in 2025). Despite this, the company has a very high growth trajectory in terms of hiring and web presence. LinkedIn reports 6 employees with +300% monthly growth, and 11 active job postings. Website traffic is growing +254.5% monthly. ## Competitive Advantages - **Founding Team & Research Pedigree**: Co-founded by Pulkit Agrawal (MIT professor, leader of the Improbable AI Lab, 2024 IEEE Early Academic Career Award) and Tuomas Haarnoja (ex-DeepMind). The team includes talent from MIT, Berkeley, Harvard, CMU, DeepMind, Microsoft, and Boston Dynamics. - **Novel Technical Approach (VFA Model)**: Their core technology, the Vision-Force-Action (VFA) model, is a claimed breakthrough that unites generality (a single model for many tasks), performance (speed and reliability), and safety (force-based interaction). This is a significant differentiator in the robotics space, which often forces a trade-off between these three attributes. - **Self-Supervised Learning & Sim-to-Real**: The company pioneers self-supervised learning and sim-to-real reinforcement learning, enabling robots to develop "common sense" and physical intuition automatically without massive amounts of human-labeled data. - **World-Class Talent Magnet**: Despite being a very early-stage startup, they are attracting top-tier talent from leading tech companies and research labs, indicating a strong technical vision and culture. ## Strategic Focus - **Productization & Deployment**: The company is actively hiring for roles across engineering, hardware, and operations, signaling a strong push to move from research to a deployable product. - **Scaling the Team**: With 11 open positions for a company of ~6 employees, the immediate strategic focus is on aggressive team building across all functions (ML, hardware, software, operations). - **Building the Foundation**: Current priorities include developing the core VFA model, building the physical robotic platform, creating robust simulation environments, and establishing operational processes for scaling. ## Why Work Here - **Cutting-Edge Mission**: Work on the frontier of embodied AI and robotics, tackling the fundamental challenge of building machines that can interact with the physical world. - **World-Class Team**: Join a team of experts from top-tier institutions (MIT, Berkeley, DeepMind, Boston Dynamics) and work alongside leaders in the field. - **High Impact, Early Stage**: As one of the first ~20 employees, you will have an outsized impact on the company's technology, culture, and direction. - **In-Office Culture**: All roles are based in Boston, MA, and are in-office, fostering close collaboration on complex hardware and software problems. - **Diverse, High-Caliber Roles**: Openings span from ML/RL engineering and simulation to mechanical design, embedded systems, and business operations, offering a wide range of challenging work. ## Sources 1. [ekarobotics.com](https://ekarobotics.com/) 2. [LinkedIn - Eka Robotics](https://www.linkedin.com/company/eka-robotics) 3. [Dealroom.co - Eka Robotics](https://app.dealroom.co/companies/eka_robotics) 4. [Built In - Eka Robotics Jobs](https://builtin.com/company/eka-robotics/jobs) 5. [Ashby - Eka Robotics Careers](https://jobs.ashbyhq.com/ekarobotics) ## Other roles at Eka - [Senior/Staff/Principal Electrical Engineer](https://feeny.ai/job/senior-staff-principal-electrical-engineer-eka-boston-e8z4fpzq6xdp) — Boston, MA - [Robotics Software Engineer](https://feeny.ai/job/robotics-software-engineer-eka-boston-5fb4fftf57eg) — Boston, MA - [Research Engineer – Simulation](https://feeny.ai/job/research-engineer-simulation-eka-boston-jtmvybfdvqmn) — Boston, MA - [Machine Learning / Computer Vision Engineer](https://feeny.ai/job/machine-learning-computer-vision-engineer-eka-boston-f2z8zq36n5vv) — Boston, MA - [Senior/Staff/Principal Mechanical Engineer](https://feeny.ai/job/senior-staff-principal-mechanical-engineer-eka-boston-gm2bz9qr8geb) — Boston, MA - [Machine Learning / Reinforcement Learning Engineer](https://feeny.ai/job/machine-learning-reinforcement-learning-engineer-eka-boston-as8ph30n88pz) — Boston, MA