Staff Machine Learning Engineer - Edge AI

About the role

The Samsara AI team builds end-to-end AI solutions for our customers as well as core ML infrastructure for Samsara. As a Staff Machine Learning Engineer, you will be working with petabyte-scale sensor, diagnostic, video, and text data to solve critical problems for Physical Operations customers, globally. You will work closely with ML Engineers and Scientists, as well as full-stack and firmware engineers to deliver core product features, services, and optimizations.

This is a remote position open to candidates residing in the United States. This position requires travel up to 5% of the time.

Responsibilities

• Lead design and implementation of critical AI product initiatives on Edge devices.
• Develop both tactical AI solutions as well as more strategic and longer term research.
• Work with petabyte-scale data from customer operations including text, transactions, diagnostics, sensor, camera, and location data.
• Partner across business units to explore and prototype new AI experiences and optimize the ML model performance on edge devices.
• Stay connected to industry and academic research and adopt novel technology that suits Samsara’s needs.
• Champion, role model, and embed Samsara’s cultural principles as we scale globally and across new offices.

Minimum Requirements

• 8+ years experience as a Machine Learning Engineer.
• Profound experience in optimizing ML models and systems for Edge compute constraints.
• Coding in Python or similar.
• Coding in C++ or Rust.
• Strong functional knowledge of the iterative machine learning product development process.
• Experienced in developing and shipping production code at large scale.
• Ability to distill informal or ambiguous customer and business requirements into crisp problem definitions.
• Proven ability to communicate verbally and in writing to technical peers and leadership teams with various levels of technical knowledge.
• Experience coaching and mentoring ML Engineers.

Ideal Candidate

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