Senior Machine Learning Engineer

Who We Are

Samsara (NYSE: IOT) is the pioneer of the Connected Operations™ Cloud, a platform enabling organizations dependent on physical operations to harness Internet of Things (IoT) data. We help improve the safety, efficiency, and sustainability of physical operations across industries like agriculture, construction, field services, transportation, and manufacturing, driving their digital transformation at scale.

Working at Samsara means you’ll define the future of physical operations, shaping product solutions like Video-Based Safety, Vehicle Telematics, Apps and Driver Workflows, and Equipment Monitoring. As part of a recently public company, you’ll have the autonomy and support to make a significant impact.

About the Senior Machine Learning Engineer Role

Samsara is a leader in AI for physical operations. We are hiring a founding Senior Machine Learning Engineer to join our growing Product ML organization. This role combines hands-on ML systems work with direct product impact. You will design and ship customer-facing ML features, including anomaly detection, crash-risk scoring, and predictive maintenance, leveraging multimodal vehicle and telematics data. You will own architectural decisions, such as online serving, streaming/batch pipelines, and feature/infrastructure tradeoffs, partnering closely with applied scientists to translate models into actionable products. This is an opportunity to shape the MLE function and potentially grow a team. This is a remote position open to candidates residing in Canada.

Why You Should Apply

• You want to impact the industries that run our world: The software, firmware, and hardware you build will have real-world impact—keeping lights on, delivering food, and ensuring worker safety.
• You want to build for scale: With over 2.3 million IoT devices deployed globally, you will innovate with new and mature technologies for customers across critical industries.
• You are a life-long learner: Samsara has ambitious goals, fostering a growth mindset as we tackle diverse technologies and challenges.
• You believe customers are more than a number: Enjoy close interaction with end-users, participating in customer interviews, collaborating with product managers, and using metrics to drive better customer outcomes.
• You are a team player: Our engineering teams thrive on a mix of independent effort and collaboration, united by our mission to achieve connected operations.

In this Senior Machine Learning Engineer role, you will:

• Founding impact & scope: Be the first dedicated MLE in a product-ML organization, influencing architecture, launching production ML products, and defining MLE partnerships with applied scientists across a 30-person data organization.
• High-value, real-world domain: Work on customer-facing systems (crash risk, anomaly detection, predictive maintenance) using rich GPS/IMU/telemetry, fleet video, and maintenance logs to directly reduce risk and save lives and operational costs.
• Systems + product blend: This role includes ML infrastructure (feature design, online serving, batch & streaming pipelines) and product ownership, covering end-to-end decisions and tradeoffs, not just model productionizing.
• Room to grow & experiment: The team encourages prototyping (including GenAI/CV layers where appropriate), and the hiring manager is open to shaping the role for senior candidates to include modeling ownership or team expansion.

Minimum Requirements for the Role:

• 5+ years experience as a Machine Learning Engineer, Applied Scientist, or similar role.
• BS or MS in Computer Science or another quantitative field.
• Strong proficiency in one or more common languages (e.g., Python, Java, C++, Golang).
• Proficiency with common ML tools and frameworks (e.g., PyTorch, TensorFlow, Spark).
• A working understanding of the algorithms you will bring to life.
• Proven experience with E2E ML application development.

An Ideal Candidate Also Has:

• Experience leading a small cross-functional team to deliver new ML experiences.
• Experience building zero-to-one ML applications.

Key skills/competency

• Machine Learning Engineering
• Applied Science
• Python
• PyTorch
• TensorFlow
• Spark
• Anomaly Detection
• Predictive Maintenance
• ML Systems Architecture
• Data Pipelines