Lead ML Infrastructure Engineer: Edge & Cloud Platform

Samsara; United States; Remote; USD 200,000 - 358,000; Full time

Benefits offered by this job

RSU program

Flexible remote model

Total rewards and benefits

Job summary

Samsara is hiring a Lead Machine Learning Infrastructure Engineer to own the architecture of our end-to-end ML platform across training, experimentation, inference, and edge deployment for Safety AI. You will bridge applied ML, firmware, security, and data platforms, shaping platform direction and enabling multiple product teams to deliver real-world safety outcomes.

You will lead the design and deployment of scalable ML systems, set reliability and security standards, and mentor senior

Qualifications

• 10+ years in ML engineering with tech lead ownership.
• Proven track record shipping ML-powered features end-to-end with measurable impact.
• Hands-on experience with Ray, Kubernetes, and Spark in production environments.

Responsibilities

• Set the technical strategy and own end-to-end delivery of Samsara’s ML platform (training, experimentation, batch/online inference, edge).
• Drive design, launch, and iteration of Safety AI features with measurable safety, reliability, and cost metrics at scale.
• Design and operate scalable online/batch inference systems (Ray, Spark) and deploy models to Samsara devices with edge-to-cloud feedback loops.
• Own reliability, observability, and security for ML systems across cloud and edge, including incident response and on-call practices.
• Be the technical authority for ML infrastructure, mentor engineers, and promote best practices and open source contributions.

Skills

Machine learning

Technical leadership

Ray

Kubernetes

Spark

Edge deployment

Tools

Ray

Kubernetes

Spark

Job description

Samsara is hiring a Lead Machine Learning Infrastructure Engineer to own the architecture of our end-to-end ML platform across training, experimentation, inference, and edge deployment for Safety AI. You will bridge applied ML, firmware, security, and data platforms, shaping platform direction and enabling multiple product teams to deliver real-world safety outcomes.

You will lead the design and deployment of scalable ML systems, set reliability and security standards, and mentor senior