Lead Machine Learning Engineer - ML Infrastructure

Overview

Lead Machine Learning Infrastructure Engineer (ML Infrastructure) to serve as the technical anchor for ML infrastructure across Samsara’s Safety AI organization.

What you'll do

• Own the architecture and evolution of an end-to-end ML platform covering training, experimentation, inference, and edge deployment.
• Set technical strategy and drive end-to-end delivery across ML platform layers for multiple Safety AI product teams.
• Design, launch, and iterate Safety AI features, co-owning outcomes including safety metrics, reliability, and cost.
• Design and operate scalable online and batch inference systems, including observability, SLOs, and training-to-production workflows.
• Partner with firmware and edge teams to package, validate, and deploy models to devices and build edge-to-cloud feedback loops.
• Own reliability, observability, and security for ML systems across cloud and edge, including on-call practices and incident response.

What you'll need

• 10+ years in machine learning engineering.
• Tech lead ownership of at least two major ML platform domains serving multiple product teams at scale.
• End-to-end shipment of ML-powered features with measurable product or business impact.
• Hands-on Ray and Kubernetes experience in production environments; Spark experience strongly preferred.
• Deep understanding of ML fundamentals including evaluation methodology, dataset design, ablation, drift.
• Cross-org technical leadership influencing platform decisions and roadmap/go-no-go calls based on trade-offs.

Details

• Remote position open to candidates based in the United States.