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Salary: USD 178,640 - 319,000 / annual
Samsara (NYSE: IOT) is building an AI/ML team within its Operations organization to make supply chain AI-native. You would be one of the first AI/ML engineers on this team, working to transform internal supply chain operations—historically run on emails, flat files, and manual reconciliations—into a modern, data-driven function.
You will design, develop, and deploy advanced machine learning and statistical models that optimize Samsara's global supply chain across fulfillment, inventory, returns, cash, planning, components, suppliers, and cost management. You'll partner directly with Planning, Procurement, Fulfillment, Finance, Sales, and hardware/firmware/quality engineering teams.
Key responsibilities include:
- Define the end-to-end AI transformation roadmap for supply chain alongside the Senior Director of Supply Chain AI Transformation, aligning with company OKRs and executive stakeholders
- Own the full modeling stack: design, MLOps, deployment, monitoring, and production systems that drive real business decisions
- Build demand, inventory, and cost forecasting systems for highly variable, seasonal SKUs with intermittent patterns and long lead times
- Model supplier risk using real-time IoT telemetry, geopolitical signals, and market data
- Design cost optimization algorithms balancing inventory carrying costs, expedite fees, and revenue risk across multiple regions
- Create anomaly detection systems for cellular connectivity spend and supply chain disruptions using multimodal data
- Establish AI/ML foundations, set modeling standards, and empower cross-functional teams to adopt data-driven decision-making
- Mentor and guide others through influence as the team scales
What makes this unique: Samsara has 11 years of untapped operational data including ERP systems (NetSuite, e2open, Propel), IoT sensor streams, Salesforce, Slack, Gong call insights, and real-world hardware telemetry. You'll have access to 10+ trillion data points annually from connected operations. The supply chain is complex—multi-tier supplier networks, long lead times, high-stakes new product introduction (NPI) ramps—and your models will help prevent supply shortages for customers in construction, utilities, transportation, and public safety. You'll optimize inventory for hardware deployed across 98% of US roads and 70+ billion miles driven annually.
You'll shape the team's roadmap, scientific agenda, and modeling standards. This is ideal for a deeply technical individual contributor who thrives in ambiguity, thinks strategically, and enjoys end-to-end ownership.
REQUIREMENTS:
- 7+ years of experience in machine learning engineering, with at least 3 years in production ML systems (modeling, MLOps, deployment, monitoring)
- Proficiency in Python and SQL; experience with ML frameworks (scikit-learn, XGBoost, PyTorch, TensorFlow) and MLOps tools (Airflow, Kubernetes, feature stores)
- Strong foundation in statistical modeling, time-series forecasting, optimization, and causal inference
- Demonstrated ability to own end-to-end ML projects from problem definition through production deployment and monitoring
- Experience building and scaling ML systems in high-stakes, mission-critical environments
- Deep understanding of supply chain concepts (S&OP, IBP, safety stock, EOQ), ERP systems (SAP, NetSuite, E2DP, Propel), and inventory optimization theory
- Ideal background in consumer electronics or B2B hardware manufacturing
- Self-directed leadership: ability to identify analytical white space, set multi-quarter plans, and mentor others through influence
- Comfort navigating trade-offs between model complexity, performance, and maintainability
