Software Engineer, Infrastructure
About Us
We are The Robotics Company, building the infrastructure that enables robots to be deployed at scale. In just six months, we’ve grown from $0 to $1M in revenue, driven by strong demand for what we’re building. We’re backed by some of the most influential leaders and operators across AI, robotics, and technology, including Dr. Marc Pollefeys; the founder of Hugging Face; leaders behind Google Maps and Android; executives from Google DeepMind and Google Cloud; robotics leaders from DeepMind and Scale AI; SV Angel; and operators from OpenAI, Anthropic, DeepMind, and more. Our mission is to build the foundational infrastructure that brings intelligent robots out of the lab and into the real world.
The Role
We’re looking for an exceptional Founding Infrastructure Engineer to build the technical foundation that takes cutting-edge robotics research from the lab into production. You’ll design and own the services, APIs, compute infrastructure, developer tooling, and security systems that connect our research stack to robots deployed in the real world. Working across cloud infrastructure, distributed systems, and robotics, you’ll define how we build, deploy, and operate our technology at scale—from the foundational architecture and internal developer platform to the production systems our customers depend on.
Key Responsibilities
Design and build the backend services, APIs, and infrastructure that power our product and production robotics deployments.
Partner closely with our robotics and vision teams to transform cutting-edge research into reliable, scalable production services.
Own and evolve CI/CD, deployment pipelines, and developer infrastructure across research and product codebases.
Make foundational backend and infrastructure architecture decisions that establish patterns and standards as the company scales.
Build the systems for versioning, testing, deploying, and monitoring trained models on real-world robotic systems.
What We're Looking For
3+ years of experience building and operating production backend systems, infrastructure, developer platforms, or SRE environments.
Strong fundamentals in distributed systems, with an understanding of reliability, scalability, and performance in production.
Hands-on experience designing and operating infrastructure on a major cloud platform, ideally AWS.
Strong proficiency in Python; experience with Go or another systems programming language is a plus.
Experience with containers, orchestration, and designing robust CI/CD pipelines.
A track record of taking prototype or research code and turning it into reliable, versioned, production-ready systems.
A high degree of ownership and comfort making foundational technical decisions in a fast-moving, early-stage environment.
Nice to Have (Not Required)
Experience with GPU clusters or ML infrastructure, including job scheduling, distributed training, and fault-tolerant compute.
Experience building internal developer platforms, tooling, or self-service infrastructure for engineering and research teams.
Experience productionizing and serving ML, computer vision, or robotics models and pipelines to external customers.
Experience as a founding or early engineer on a small, fast-moving technical team.
Experience supporting research environments where reproducibility, experimentation speed, and reliable production systems all matter.
Why Join Us?
This is a rare opportunity to work alongside some of the world’s top researchers and engineers in robotics and AI, building the systems that will move intelligent robots out of the lab and into the real world.
We’re at an inflection point. In just six months, we’ve grown from $0 to $1M in revenue, and we’re rapidly scaling our team across San Francisco and Zurich as we tackle increasingly ambitious problems in robot learning, manipulation, and real-world deployment.
If you’re looking for a mature organization with narrowly defined problems and established playbooks, this may not be the place for you.
If you want to join early, work at the frontier of robotics and embodied AI, and help build the foundational technology that enables robots to operate intelligently and reliably at scale — this is it!
