Lead Machine Learning Engineer - ML Infrastructure

Responsibilities

• ML Platform & Infrastructure
• Set the technical strategy and own end-to-end delivery of Samsara's ML platform (training, experimentation, batch/online inference, edge) — making architectural decisions and being the accountability point across all platform layers for multiple Safety AI product teams.
• Experimentation & Measurement
• Drive the design, launch, and iteration of Safety AI features (CV models, EcoDriving insights, LLM-based reporting) — not just enabling others to ship, but co-owning outcomes including safety metrics, reliability, and cost at production scale.
• Inference & Edge Deployment
• Design and operate scalable online and batch inference systems (Ray, Spark), including deployment patterns, observability, SLOs, and unified training-to-production workflows.
• Partner with firmware and edge teams to package, validate, and deploy models to Samsara devices, and build feedback loops from edge to cloud for continuous improvement.
• Reliability, Security & Operations
• Own reliability, observability, and security for ML systems across cloud and edge, including on-call practices, incident response, and infrastructure hardening.
• Own or co-own end-to-end technical delivery for high-priority or high-risk initiatives, from modeling and system design through production rollout.

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