Job Description
A Machine Learning Engineer at Samsara develops and deploys customer-facing ML features for IoT-based physical operations, focusing on real-world impact such as safety, predictive maintenance, and operational efficiency, while owning end-to-end system architecture and collaborating with cross-functional teams.
Key Responsibilities
- Design and ship customer-facing ML features such as anomaly detection, crash risk scoring, and predictive maintenance.
- Own architectural decisions for online serving, streaming, batch pipelines, and features infrastructure.
- Collaborate with applied scientists to turn models into actionable products.
- Influence ML system architecture, launch production ML products, and define team partnerships within the data organization.
- Develop and maintain ML infrastructure, including feature design, online serving, and data pipelines.
Requirements
- Minimum of 5 years experience as a Machine Learning Engineer, Applied Scientist, or similar role.
- Bachelor's degree (BS) or Master's degree (MS) in Computer Science or another quantitative field.
- Strong proficiency in one or more common programming languages such as Python, Java, C++, or Golang.
- Proficiency with common machine learning tools and frameworks such as PyTorch, TensorFlow, or Spark.
- A working understanding of the algorithms you will bring to life.
- Proven experience with end-to-end machine learning application development.
- Experience leading a small cross-functional team to deliver new machine learning experiences (preferred but not explicitly mandatory).
- Experience building zero-to-one machine learning applications (preferred but not explicitly mandatory).
Benefits & Perks
Annual base salary between 157,250 and 203,500 CAD
Initial RSU grant with no vesting cliff and ongoing refresh opportunities tied to performance
Performance-based bonus variable pay
Equity for eligible roles
Flexible, employee-led remote work model
Comprehensive health and parental leave plans
Professional development stipend
Ready to Apply?
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