[Hiring] Staff Machine Learning Engineer @Samsara

Role Description

Samsara is building an AI/ML team inside its Operations team to make our supply chain AI native. You would be one of its first AI/ML engineers.

• Design connected hardware (cameras, vehicle gateways, sensors) and deliver it to tens of thousands of customers.
• Work across the supply chain including fulfillment, inventory, returns, cash, planning, components, suppliers, and cost management.
• Partner directly with Planning, Procurement, Fulfillment, Finance, Sales, and engineering teams.
• Design, develop, and deploy advanced machine learning and statistical models that optimize our global supply chain.
• Apply cutting-edge techniques to solve complex problems with direct business impact.

Qualifications

• 8+ years in applied data science or ML, ideally in supply chain, operations research, logistics, or manufacturing.
• Master's or PhD in Computer Science, Statistics, Data Science, EE, OR, or related technical field.

Requirements

• Expert in statistical modeling and ML: time series forecasting, optimization, anomaly detection, causal inference.
• Strong Python coding skills and fluency in SQL; proven experience developing and deploying production ML systems.
• Proficiency in MLOps practices: automated testing, CI/CD, model versioning, monitoring, performance tracking.
• Experience building real-time inference pipelines and managing GPU/TPU resources for training at scale.
• Familiar with data visualization tools (Tableau, Power BI) and cloud platforms (AWS, GCP, Azure).

Benefits

• Real-world impact at massive scale: models will help prevent supply shortages for customers in construction, utilities, transportation, and public safety.
• Optimize inventory for hardware deployed across 98% of US roads and 70+ billion miles driven annually.
• Drive sustainability initiatives by reducing waste and improving supply chain efficiency across global operations.

Company Description

Samsara (NYSE: IOT) is the pioneer of the Connected Operations™ Cloud, enabling organizations that depend on physical operations to harness IoT data for actionable insights and improved operations.