About Menlo
Menlo Research is an Applied R&D lab building Asimov, an open-source humanoid robot platform, and the full software stack that powers it. Our mission is to make humanoid labor economically viable -- turning software into physical labor at scale. We build across the full stack: hardware architecture, locomotion, autonomy, simulation, and infrastructure. We move fast, ship to real robots, and open-source everything we can. If you want your work to matter beyond a paper or a demo, this is the place.
The Role
We are looking for a Platform Engineer to build and maintain the infrastructure and data systems that power Asimov and Menlo's developer platform. You will work across cloud infrastructure, data pipelines, and production APIs -- keeping our systems reliable, scalable, and fast as our robot fleet and developer ecosystem grow. This is a hands-on engineering role for someone who is as comfortable debugging a flaky pipeline as they are designing a new ingestion architecture.
What You'll Do
Build and maintain distributed infrastructure handling telemetry, sensory, and control data across cloud and edge environments
Design and operate data ingestion and streaming pipelines connecting robot fleets to the cloud in real time, covering video, joint states, audio, and LiDAR
Develop and maintain backend services and APIs that power Menlo's developer-facing platform, with a focus on reliability and developer experience
Manage and evolve cloud native infrastructure using Kubernetes, Docker, and infrastructure as code tooling
Ensure platform reliability through monitoring, alerting, autoscaling, failover, and incident response
Support ML and robotics teams with data infrastructure for training pipelines, policy rollout, and hardware-in-the-loop simulation
Implement secure APIs with access control, rate limiting, and usage metering as we scale
What You'll Bring
4 or more years of professional software engineering experience in platform, infrastructure, or data engineering
Proficiency in one or more of Go, Rust, Python, or TypeScript, with strong fundamentals in concurrency and systems performance
Hands-on experience with cloud native tooling: Kubernetes, Docker, Helm, and gRPC
Experience building and operating data pipelines and streaming systems -- Kafka, Flink, or similar
Solid understanding of API design patterns including REST, gRPC, and WebSockets
Experience with databases spanning PostgreSQL, Redis, and modern vector databases
Familiarity with observability tooling: Prometheus, Grafana, Datadog, or OpenTelemetry
Bonus Points
Experience with real-time data streams from physical sensors or robotics systems
Familiarity with MLOps workflows including model versioning, inference pipelines, and model registries
Background in distributed training or large-scale simulation infrastructure
Contributions to open-source infrastructure, robotics middleware, or AI frameworks
Experience on developer platforms or API products
Why Join Menlo?
Platform and data engineering at most companies means keeping the lights on for someone else's product. At Menlo, the platform is core to what we ship -- it is how robots learn, how developers build on top of us, and how we close the loop between simulation and the real world. You will work on systems that are genuinely hard, with direct visibility into how your infrastructure shapes the robots we deploy. If you want ownership and real problems, this is the place.
A Note on AI
You don't need deep AI expertise for every role, but we do expect everyone at Menlo to be intellectually curious, drawn to tinkering and discovery, and excited to use AI as a real collaborator in their work. For some roles, AI fluency is a core requirement. When that's the case, we'll say so explicitly in the qualifications. People who thrive here don't treat AI as a novelty. They use it to think better, and make their work easier for others to build on.
Equal Opportunity and Accommodations
We hire talented people from a wide range of backgrounds. If you're excited about a role but don't meet every bullet, we still encourage you to apply. Research is an equal opportunity employer and does not discriminate on the basis of any legally protected characteristic. provides reasonable accommodations during the application process. If you need one, please let your recruiter know.
Originally posted on