Staff Machine Learning Engineer - Edge AI

Samsara (NYSE: IOT) is the pioneer of the Connected Operations Cloud, a platform that enables organizations that depend on physical operations to harness IoT data for actionable insights. They serve industries like agriculture, construction, field services, transportation, and manufacturing, helping improve safety, efficiency, and sustainability.

As a Staff Machine Learning Engineer on the Samsara AI team, you will work with petabyte-scale sensor, diagnostic, video, and text data to solve critical problems for Physical Operations customers. You will collaborate with ML Engineers, Scientists, and full-stack and firmware engineers to deliver core product features and optimizations. This is a remote position open to candidates in the United States, with up to 5% travel required.

• Lead design and implementation of critical AI product initiatives on Edge devices.
• Develop tactical AI solutions and strategic long-term research.
• Work with petabyte-scale data from customer operations.
• Partner across business units to prototype new AI experiences and optimize ML model performance on edge devices.
• Stay connected to industry and academic research and adopt novel technology.

• 8+ years experience as a Machine Learning Engineer.
• Profound experience optimizing ML models for Edge compute constraints.
• Coding in Python or similar.
• Coding in C++ or Rust.
• Strong functional knowledge of iterative ML product development.
• Experience shipping production code at large scale.
• Ability to distill ambiguous requirements into crisp problem definitions.
• Proven communication skills to technical and leadership audiences.
• Experience coaching and mentoring ML Engineers.

• Proficiency in self-serving data for experiments and model training at scale.
• Established record of high-impact AI deliveries.
• Deep knowledge in state-of-the-art Computer Vision and multi-model models.

Annual base salary range: $178,640—$319,000 USD. Eligible for initial RSU grant with no vesting cliff and ongoing refresh opportunities.

Performance-based bonus/variable pay, equity, comprehensive health and parental leave plans, professional development stipend, and a flexible, employee-led remote model.

Apply via the provided link.