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Menlo Research

Platform Lead

Posted 13 Hours Ago
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In-Office
Singapore
Senior level
In-Office
Singapore
Senior level
Lead the evolution of infrastructure for robotics and AI platforms by architecting distributed systems, handling data processing, and ensuring platform reliability. Collaborate across teams to enhance developer experience.
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About Asimov
Asimov is Menlo's open source humanoid robotics platform, building every layer from structural frames and electromechanical assemblies to power electronics, embedded control hardware, firmware, and AI. We also build Jan, our open source AI assistant used by millions of developers worldwide. Our goal is to democratize advanced robotics and AI by sharing designs, models, and infrastructure with the global community.

The Role We are looking for a Platform Lead to own and evolve the full infrastructure stack that powers both our humanoid robotics fleet and our developer facing AI platform. This is a senior technical leadership role sitting at the intersection of distributed systems, high performance APIs, and production AI infrastructure. You will work directly with the founders and technical leadership to design systems that let hundreds of robots learn and act as one, while also enabling developers and partners to build on top of Menlo's intelligent platform. If you thrive on hard technical problems at massive scale and want genuine ownership over platform architecture, this role is for you.
What You'll Do

  • Architect and scale distributed systems that handle petabytes of sensory, telemetry, and control data across cloud and edge environments, connecting fleets of robots in real time.
  • Design and build the Menlo API Platform, delivering high reliability, world class developer experience, and production grade multimodal AI capabilities via intuitive APIs and SDKs.
  • Build large scale training and inference platforms for multimodal foundation models powering robot autonomy, teleoperation, and developer integrations.
  • Design data ingestion and streaming pipelines connecting robot fleets to the cloud in real time, covering video, LiDAR, joint states, and audio.
  • Manage and evolve a modern cloud native infrastructure stack using Kubernetes, Docker, and infrastructure as code tooling.
  • Ensure platform reliability through telemetry, monitoring, alerting, autoscaling, failover, and disaster recovery mechanisms.
  • Lead infrastructure decisions spanning distributed storage, consensus protocols, GPU orchestration, network reliability, and API security.
  • Collaborate across ML, robotics, and product teams to support hardware in the loop simulation, policy rollout, continuous learning, and CI/CD workflows.
  • Implement secure APIs with fine grained access control, usage metering, rate limiting, and billing integration as we scale to serve millions of users.

What You'll Bring

  • 7 or more years of professional software engineering experience with deep expertise in distributed systems, backend infrastructure, or data platforms.
  • Proven ability to build and operate production grade systems handling massive scale and mission critical workloads.
  • Proficiency in Go, Rust, C++, Python, or TypeScript, with strong fundamentals in concurrency, networking, and systems performance.
  • Deep experience with cloud native architectures including Kubernetes, Docker, Helm, gRPC, Kafka, Ray, and service mesh technologies such as Istio or Linkerd.
  • Strong understanding of API architecture and design patterns including REST, gRPC, WebSockets, OAuth2, and OpenAPI.
  • Experience with databases spanning PostgreSQL, Redis, and modern vector databases such as Pinecone, Weaviate, or FAISS.
  • Strong understanding of data consistency, replication, and fault tolerance across heterogeneous environments.
  • Familiarity with observability tooling such as Prometheus, Grafana, Datadog, or OpenTelemetry applied to large scale production systems.

Bonus Points

  • Experience building distributed training, large scale simulation, or fleet scale telemetry systems.
  • Familiarity with real time robotics workloads including streaming from physical sensors and actuators.
  • Experience with MLOps tools and AI workflows including model versioning, inference pipelines, and model registries.
  • Knowledge of billing systems, quota enforcement, chargeback models, and multi tenant security and isolation.
  • Prior experience on developer platforms or API products with a strong focus on developer UX and documentation.
  • Contributions to open source infrastructure, AI frameworks, or robotics middleware such as ROS, gRPC, or Mediasoup.

Why Join Menlo? You will be part of a tight knit team defining the next generation of humanoid robots and open AI infrastructure. With genuine ownership over platform architecture and the freedom to make bold technical decisions, you will see your systems power real robots in real world deployments. If you thrive in fast paced, open collaborative environments and want to build infrastructure that actually matters, let's build the future of robotics together.

Top Skills

C++
Datadog
Docker
Faiss
Go
Grafana
Grpc
Helm
Istio
Kafka
Kubernetes
Linkerd
Opentelemetry
Pinecone
Postgres
Prometheus
Python
Ray
Redis
Rust
Typescript
Weaviate

Menlo Research Singapore Office

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