Drimva

Rhoda AI

Software Engineer, Inference Infrastructure

$175K–$280K

Mountain View · Full-time · Posted May 12, 2026

Experience
3+ years in ML infrastructure, MLOps, or distributed systems.

About the job

Build and operate scalable infrastructure for deploying and serving foundation-model workloads across cloud and on-prem environments.

What you'll do

  • Design and operate infrastructure for model workloads across cloud and on-prem environments.
  • Build Kubernetes deployment pipelines and manage GPU resource scheduling and orchestration.
  • Integrate model-serving systems and develop tooling for deployment, versioning, and observability.

What they ask for

  • Strong proficiency with Kubernetes and containerized deployment pipelines.
  • Experience with GPU orchestration and resource scheduling across large distributed jobs.
  • Experience with cloud providers and hybrid cloud/on-prem infrastructure.
  • Familiarity with ML frameworks and model-serving tools; strong debugging and ownership skills.

Nice to have

  • Experience with streaming systems or high-throughput data transport.
  • Background in networking, low-latency systems, edge/cloud deployment, embedded inference, or cluster scheduling systems.

Pay

$175K – $280K (base salary)

Tools

Kubernetes, AWS, GCP, PyTorch, JAX, Triton, Ray Serve, TorchServe

AI focus

Infrastructure for deploying and serving large foundation models, including distributed ML workloads and inference.

Model-written summary · the original posting is authoritative

First seen Oct 29, 2026 · Last verified Nov 5, 2026 (UTC)