Samsara is hiring a remote Staff ML Engineer Edge AI!
Samsara is hiring a Staff Machine Learning Engineer for Edge AI to lead the design and delivery of AI capabilities that run on devices in physical operations. The role sits with an AI team working across enormous streams of sensor, video, text, diagnostic and location data, turning customer and business needs into practical ML products while also pursuing longer-range research. The engineer will collaborate with ML scientists, full-stack and firmware engineers, and influence model performance under edge constraints. This is a remote role open to Canada-based candidates, with occasional travel and no relocation support.
Key responsibilities
- Lead the design and implementation of major edge AI product initiatives.
- Build near-term ML solutions while also exploring strategic, longer-range research.
- Work with very large operational datasets spanning text, transactions, diagnostics, sensors, cameras and location.
- Partner with teams across the business to prototype new AI experiences and improve model performance on constrained devices.
- Track academic and industry advances and apply promising techniques where they fit Samsara’s needs.
- Coach and mentor machine learning engineers and model Samsara’s cultural principles.
Key requirements
- 8+ years of experience as a machine learning engineer.
- Strong record optimizing ML models and systems for edge compute limits.
- Programming ability in Python or a similar language.
- Programming ability in C++ or Rust.
- Solid understanding of the iterative ML product development process.
- Experience shipping production code at large scale.
- Ability to turn ambiguous customer or business needs into clear problem statements.
- Strong written and verbal communication with technical peers and leadership.
- Experience coaching and mentoring ML engineers.
- Seniority: Staff
- Work mode: Remote in Canada; up to 5% travel
- Salary: $170,400–$234,300 CAD annually
- Key skills: Python, C++, Rust, edge ML optimization, computer vision, multimodal models, large-scale production ML, mentoring
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