Staff Machine Learning Engineer - Edge AI

Samsara Samsara · Enterprise · San Francisco, CA · Platform

Staff Machine Learning Engineer focused on designing and implementing AI products on Edge devices, optimizing ML models for edge compute constraints, and working with large-scale sensor, diagnostic, video, and text data for industrial operations. The role involves both tactical solutions and strategic research, with a strong emphasis on production code delivery and cross-functional collaboration.

What you'd actually do

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

Skills

Required

  • 8+ years experience as a Machine Learning Engineer
  • Optimizing ML models and systems for Edge compute constraints
  • Spark, Ray, or a similar framework
  • Python
  • C++ or Rust
  • Iterative machine learning product development process
  • Developing and shipping production code at large scale
  • Distill informal or ambiguous customer and business requirements into crisp problem definitions
  • Communicate verbally and in writing to technical peers and leadership teams
  • Coaching and mentoring ML Engineers

Nice to have

  • Self-serving with data for experiments and model training at scale
  • Successful high impact deliveries in AI
  • Deep knowledge in state of the art Computer Vision and multi-model models

What the JD emphasized

  • optimize ML models and systems for Edge compute constraints
  • coding in C++ or Rust
  • developing and shipping production code at large scale
  • Deep knowledge in state of the art Computer Vision and multi-model models

Other signals

  • Edge AI
  • ML infrastructure
  • petabyte-scale data
  • production code at large scale
  • optimize ML models for Edge compute constraints