Staff Machine Learning Infrastructure Engineer
Cssmerge · San Francisco, CA
About this role
**Who we are** Atoms is building the machines that power the next era of progress—real-world robots for industries that move civilization forward (starting with food, mining, and transport). We integrate across hardware, software, AI, operations, manufacturing, and real estate. We deploy systems into real environments, operate them, learn from them, and improve them until they work at scale. **What you’ll do** We’re seeking a **Staff Machine Learning Infrastructure Engineer** to design and build large-scale ML training infrastructure for next-generation autonomous transport models. In this role, you’ll: - Design and scale repeatable ML infrastructure using **Kubernetes** for large-scale distributed GPU training. - Use distributed compute frameworks to manage and execute many concurrent ML training jobs across large GPU clusters. - Integrate **MLOps** and experiment tracking for deep observability into training metrics and run performance. - Build and optimize high-throughput data ingestion pipelines to stream petabyte-scale multi-sensor vehicle logs into training environments. - Architect validation infrastructure for autonomous model validation and continuous integration testing to ensure regression-free vehicle policy releases. - Partner with robotics engineers and ML researchers to remove workflow bottlenecks and accelerate the deploy-to-vehicle lifecycle. **What we’re looking for** - **8+ years** of professional software engineering experience - Strong backend systems skills (Go, Python, Java, or similar; Rust exposure is a plus) - Proficiency with **Kubernetes** and building cloud-agnostic environments - Experience with distributed ML compute frameworks (e.g., **Ray**) for multi-node GPU workloads - Hands-on MLOps experience (metadata tracking, model registries) using tools like **MLflow** - Experience building high-throughput data pipelines using modern distributed data engines **Why join us** Work on one of the defining challenges of our time: bringing automation into the physical world with real, lasting impact. The work is ambitious and challenging, grounded in a shared purpose and a team committed to seeing it through. **What else you need to know** - **Location:** San Francisco office (onsite, five days a week) - **Base salary range:** **$224,000 - $280,000/year** - Actual compensation varies by experience, skills, and qualifications; equity may be available. - **Benefits (USA Full-Time Exempt Employees):** Medical/Dental/Vision/Disability/Life, FSA/HSA options, 401(k), equity, sick time + unlimited flexible time off + paid holidays, paid parental leave, commuter benefits, and team lunch in SoMa office Tuesdays & Thursdays. **#LI-Onsite**
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