Infrastructure Engineer

About Menlo

Menlo Research is an Applied R&D lab building the software and hardware stack for the humanoid century. Our products span Asimov, an open-source humanoid robot, and Menlo OS, an integrated platform for embodied AI development. We run serious compute infrastructure to support sim-to-real pipelines, hardware-in-the-loop testing, and large-scale model training. We move fast, publish our work, and build for decades.

The Role

As an Infrastructure Engineer, you will own and evolve the platform that everything at Menlo runs on, from inference serving to training rigs to the agentic coding infrastructure that powers day-to-day engineering. You will work deep in the stack, across OpenStack, Kubernetes, and bare metal, and set the technical direction for how Menlo Cloud scales.

What You'll Do

Own and operate Menlo Cloud: OpenStack Nova compute, Neutron networking, Trove database services, across Prod, Dev, and Sysadmin clusters

Manage Kubernetes clusters via Cluster API and kubeadm, including control plane operations, node lifecycle, and cluster upgrades

Manage and improve our inference platform: vLLM serving, AIBrix for multi-model orchestration and autoscaling across a fleet of NVIDIA GPUs

Build and maintain autoscaling at every layer: Cluster Autoscaler, HPA, and KEDA for event-driven workload scaling

Operate platform services: Kafka, Redis, PostgreSQL, OpenSearch, Prometheus

Own the observability stack: Grafana, Mimir, Tempo, Loki, Pyroscope, OnCall, one pane of glass across all clusters

Manage GitOps deployments via ArgoCD and identity via Keycloak integrated with Google Workspace

Harden network security across private load balancers, firewalls, and VPC segmentation

Support training infrastructure: self-service VM provisioning, RunPod burst capacity, Weights and Biases integration

Drive infrastructure reliability, cost efficiency, and capacity planning as the platform scales

What We're Looking For

5+ years of hands-on infrastructure engineering experience in production environments

Extensive experience with OpenStack in production: Nova, Neutron, Cinder, Trove, Horizon, and CLI administration

Strong Kubernetes experience without managed control planes: Cluster API, kubeadm, self-managed clusters

Deep Linux proficiency: RHEL, Ubuntu, or equivalent, including kernel-level debugging and performance tuning

Experience with infrastructure-as-code and automation: Ansible, Terraform, or equivalent

Familiarity with GPU infrastructure: inference serving, vLLM, model orchestration, and cluster management

Solid understanding of GitOps workflows and tools like ArgoCD

Experience with observability: Prometheus, Grafana, distributed tracing, log aggregation

Strong networking fundamentals: VPCs, firewalls, load balancers, private cluster architecture

Comfort operating in a high-ownership environment where you make architecture decisions and move fast

Bonus points for:

Experience with KVM virtualization and storage backends like Ceph

Familiarity with vLLM internals: PagedAttention, continuous batching, tensor parallelism

Experience with KEDA or event-driven autoscaling patterns

Background in AI/ML infrastructure or GPU cluster operations at scale

Prior open-source contributions to OpenStack, Kubernetes, or adjacent projects

Why Join Menlo?

Most infrastructure teams manage someone else's cloud. At Menlo, you own the metal. Menlo Cloud is a first-class investment built from the ground up, and it sits at the center of everything we do, from coding agents to humanoid robots. You will have genuine ownership over a platform that is technically ambitious, cost-conscious by design, and critical to the mission. If you want to build infrastructure that actually matters and have the autonomy to do it right, this is the place.