ML Engineer - ML Infrastructure

Overview

Who We Are Samsara (NYSE: IOT) is the pioneer of the Connected Operations™ Cloud, which is a platform that enables organizations that depend on physical operations to harness Internet of Things (IoT) data to develop actionable insights and improve their operations. At Samsara, we are helping improve the safety, efficiency and sustainability of the physical operations that power our global economy.

Representing more than 40% of global GDP, these industries are the infrastructure of our planet, including agriculture, construction, field services, transportation, and manufacturing — and we are excited to help digitally transform their operations at scale.

Working at Samsara means you’ll help define the future of physical operations and be on a team that’s shaping an exciting array of product solutions, including Video-Based Safety, Vehicle Telematics, Apps and Driver Workflows, and Equipment Monitoring. As part of a recently public company, you’ll have the autonomy and support to make an impact as we build for the long term.

About the role Samsara is the industry leader in AI for physical operations. We’re hiring a Staff / Senior Staff Machine Learning Infrastructure Engineer to lead the design and evolution of our end-to-end ML platform powering Safety AI and adjacent product areas. This role combines deep platform ownership with direct product impact—enabling teams to build, deploy, and scale ML systems that improve real-world safety outcomes.

This is a remote position open to candidates based in the United States.

• Design, build, and operate Samsara’s end-to-end ML platform spanning training, experimentation, batch and online inference, and edge deployment, used by multiple product teams across Safety AI and adjacent domains.
• Partner with product and applied ML teams to design, launch, and iterate ML-powered features (e.g., backend CV models, Eco Driving insights, LLM-based reporting), driving measurable improvements in safety outcomes, feature reliability, and cost efficiency.
• Lead throughput and cost estimation for new ML features—from early-stage exploration to production-scale capacity planning—informing roadmap and go/no-go decisions.
• Collaborate on experiment design and evaluation, including defining success metrics, structuring A/B tests or offline evaluations, and interpreting results to guide product and technical decisions.
• Evolve shared training and experimentation infrastructure (e.g., job orchestration, cluster configuration, environment management), and standardize experiment tracking, evaluation, and regression testing to enable fast and safe iteration.
• Design and operate scalable online and batch inference systems (Ray- and Spark-based), including deployment patterns, observability, and SLOs, while unifying training-to-production workflows and enabling consistent pipelines across teams.
• Partner with firmware and edge teams to define workflows for packaging, validating, and deploying models to Samsara devices, and build feedback loops from edge to cloud to support continuous improvement.
• Own the reliability, observability, and security posture of ML systems across cloud and edge environments, including on-call practices, incident response, and infrastructure hardening.
• Provide Staff+/Senior-Staff-level technical leadership by setting architecture and strategy for ML infrastructure, influencing cross-team decisions, and mentoring engineers and applied scientists.
• Drive strong developer experience through documentation, office hours, and best practices, while contributing to and representing Samsara in open source communities (e.g., Ray, Spark, RayDP).
• Own or co-own end-to-end technical delivery for high-priority or high-risk initiatives, from modeling and system design through production rollout.
• Champion, role model, and embed Samsara’s cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices.

• 10+ years of overall experience in machine learning engineering or related fields, with a strong track record of building and…