Job Description
The role involves designing and deploying advanced machine learning models to optimize Samsara's global supply chain, including demand forecasting, inventory management, and supply risk modeling, while collaborating cross-functionally and ensuring scalable, operational AI solutions.
Key Responsibilities
- Design, develop, and deploy advanced machine learning and statistical models for supply chain optimization
- Build predictive models for demand forecasting, inventory optimization, and supply risk assessment
- Create data pipelines and ETL processes using large-scale ERP, IoT, and third-party datasets
- Implement production-grade ML systems supporting batch and real-time inference with MLOps best practices
- Collaborate with cross-functional teams to align data requirements, integration, and deployment strategies
- Enhance data infrastructure and analytics platforms for real-time model training, monitoring, and inference
- Mentor junior data scientists through code reviews and collaborative projects
- Establish governance, documentation, and quality standards for model development and lifecycle management
- Identify data, tools, and process gaps and lead initiatives to address them
- Partner with operations management to promote adoption of AI tools and insights-driven workflows
Requirements
- 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, Electrical Engineering, Operations Research, 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, with experience developing and deploying production machine learning 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 such as Tableau or Power BI and cloud platforms such as 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.
- Ability to design and validate experiments, including A/B testing, multi-armed bandits, and applying Bayesian methods for uncertainty quantification.
- Proven experience building advanced forecasting models such as Prophet, LSTMs, or Transformer-based models for intermittent demand and seasonal patterns.
- Skilled in profiling machine learning workloads and reducing cloud GPU spend through model compression, quantization, pruning, and serverless architectures.
- Demonstrated ability to deploy low-latency inference across multiple geographic regions with fail-over and disaster-recovery strategies.
- Experience evaluating and integrating third-party ML platforms and contributing to or leveraging open-source projects.
Benefits & Perks
Competitive total compensation package including base salary, bonus, variable pay, and restricted stock unit awards (RSUs)
Remote and flexible working arrangements
Health benefits
Opportunities for career growth and development
Inclusive work environment with accommodations for persons with disabilities
Ready to Apply?
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