Atoms
Staff Machine Learning Infrastructure Engineer
$224K–$280K
San Francisco, CA +1 · Staff · Full-time · Posted Jul 1, 2026
- Location
- San Francisco, CA
San Francisco, California, United States - Experience
- 8+ years of professional software engineering career experience.
About the job
Builds scalable, cloud-agnostic machine-learning training and validation infrastructure for autonomous transport models, enabling researchers to run and monitor distributed GPU workloads and deploy models to vehicles.
What you'll do
- Design and scale Kubernetes-based infrastructure for distributed GPU training and concurrent ML jobs.
- Build experiment-tracking, MLOps, and high-throughput data pipelines for petabyte-scale vehicle logs.
- Develop infrastructure for autonomous-model validation and continuous integration, collaborating with robotics and ML teams.
What they ask for
- 8+ years of professional software engineering experience.
- Strong backend systems programming skills in Go, Python, Java, or similar.
- Proficiency with Kubernetes and building cloud-agnostic environments.
- Experience with distributed ML compute frameworks, MLOps pipelines, model registries, and high-throughput data pipelines.
Nice to have
- Familiarity with or exposure to Rust.
Pay
$224,000 - $280,000 per year (base salary)
Tools
Kubernetes, Go, Python, Java, Rust, Ray, MLflow
AI focus
Infrastructure for training, tracking, and validating autonomous transport models using distributed GPU workloads and vehicle sensor data.
Model-written summary · the original posting is authoritative