
Senior AI/ML Engineer - Supply Chain
- Los Angeles, CA
- Permanent
- Full-time
- You are motivated by impact: Your work will drive smarter, faster, and more sustainable supply chain decisions across Samsara's operations.
- You combine scientific rigor with real-world pragmatism: You're skilled at navigating trade-offs between model complexity, performance, and maintainability.
- You want to work on hard problems: You'll help tackle forecasting volatility, cost optimization, anomaly detection, and more using large, noisy, high-dimensional datasets.
- You are a self-directed leader: You identify analytical white space, set multi-quarter plans, and mentor others through influence.
- You enjoy building models that matter: Your solutions will be deployed in production, drive decisions, and be regularly evaluated against business KPIs.
- Define the end-to-end AI transformation roadmap for supply chain alongside the Director, aligning with company OKRs and working closely with executive stakeholders.
- Own the design, training, validation, and deployment of ML and statistical models.
- Create novel features using large-scale ERP, IoT, and third-party datasets; build pipelines and ETL jobs to serve models and stakeholders.
- Deliver production-grade code that supports both batch and real-time inference with MLOps best practices.
- Act as the AI liaison to Product, Engineering, Procurement, and Finance-ensuring alignment on data requirements, integration, and change management.
- Drive enhancements to our data infrastructure and analytics platform to support real-time model training, monitoring, and inference at scale.
- Mentor junior scientists through code reviews and collaborative project work.
- Act as a key scientific voice in roadmap planning, experimentation frameworks, and modeling strategy discussions.
- Identify gaps in data, tools, and processes-and lead initiatives to close them.
- Establish governance frameworks, documentation standards, and quality controls for model development, validation, and lifecycle management.
- Partner with Ops management to drive adoption of AI tools, define new processes, and train supply chain teams on insights-driven workflows.
- Hire, develop and lead an inclusive, engaged, and high-performing team.
- Champion, role model, and embed Samsara's cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices.
- 8+ years of experience in applied data science or machine learning, ideally in supply chain, operations research, logistics, or manufacturing.
- Master's or PhD in Computer Science, Statistics, Data Science, EE, OR, or a related technical field.
- Expertise in statistical modeling or machine learning, including time series forecasting, optimization, and anomaly detection.
- Strong coding skills in Python and fluency in SQL; experience developing and deploying production ML systems.
- Familiarity with MLOps practices, including automated testing, CI/CD, model versioning, and monitoring.
- Demonstrated track record building real-time inference pipelines and managing GPU/TPU resources.
- Familiarity with data visualization tools (e.g., Tableau, Power BI) and cloud platforms (e.g., AWS, GCP, or Azure).
- A passion for operational excellence, cost efficiency, and building scalable, data-driven solutions.
- Exceptional problem-solving, critical thinking, and communication abilities.
- Deep Statistical Expertise: Able to design and validate experiments (A/B, multi-armed bandits) and apply Bayesian methods for uncertainty quantification.
- Time-Series Mastery: Proven track record building advanced forecasting models (e.g., Prophet, LSTMs, Transformer-based) for intermittent demand and seasonal patterns.
- Cost Optimization Mindset: Skilled in profiling ML workloads and driving down cloud/GPU spend through model compression (quantization, pruning) and serverless architectures.
- Cross-Region Scaling: Demonstrated ability to deploy low-latency inference across multiple geographic regions with fail-over and disaster-recovery strategies.
- Vendor & Open-Source Savvy: Experience evaluating and integrating third-party ML platforms and contributing to or leveraging relevant open-source projects.