Platform Engineer

📋 Job Overview

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.

🏢 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.

✅ Key Responsibilities

• 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

📌 Required Qualifications

• 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

⭐ Desirable Experience

• 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

🎁 Benefits

Menlo Research is an equal opportunity employer and does not discriminate on the basis of any legally protected characteristic. Menlo provides reasonable accommodations during the application process.

🛂 Visa & Eligibility

Menlo Research is an equal opportunity employer and does not discriminate on the basis of any legally protected characteristic.