ML Engineer - ML Infrastructure
Cape Coral, Lee County, Florida, 33904, USA
Listed on 2026-06-04
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Software Development
AI Engineer, Machine Learning/ ML Engineer
Who we are
Samsara (NYSE: IOT) is the pioneer of the Connected Operations Cloud, 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.
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.
Aboutthe 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.
You should apply if:
- You want to impact the industries that run our world: The software, firmware, and hardware you build will result in real‑world impact—helping keep the lights on, get food into grocery stores, and most importantly, ensuring workers return home safely.
- You want to build for scale: With over 2.3 million IoT devices deployed to our global customers, you will work on a range of new and mature technologies driving scalable innovation for customers across industries driving the world's physical operations.
- You are a life‑long learner: We have ambitious goals. Every Samsarian has a growth mindset as we work with a wide range of technologies, challenges, and customers that push us to learn on the go.
- You believe customers are more than a number: Samsara engineers enjoy a rare closeness to the end user and you will have the opportunity to participate in customer interviews, collaborate with customer success and product managers, and use metrics to ensure our work is translating into better customer outcomes.
- You are a team player: Working on our Samsara Engineering teams requires a mix of independent effort and collaboration. Motivated by our mission, we’re all racing toward our connected operations vision, and we intend to win‑together.
- Design, build, and operate Samsara’s end‑to‑end ML platform (training, experimentation, batch/online inference, edge) used by multiple Safety AI product teams.
- Evolve shared training and experimentation infrastructure (orchestration, clusters, environments) and standardize tracking, evaluation, and regression testing for fast, safe iteration.
- Partner with product and applied ML teams to ship ML‑powered features (CV models, Eco Driving insights, LLM‑based reporting) that improve safety, reliability, and cost efficiency.
- Lead throughput and cost modeling for new ML features—from exploration to production‑scale capacity planning—to inform roadmap and go/no‑go decisions.
- Drive experiment design and evaluation
, defining success metrics, structuring A/B or offline tests, and turning results into product and technical decisions.
- 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.
- 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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