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Machine Learning for Supply Chain

2 months, 1 week ago
United States, Canada
Full-time
Lead
Machine Learning Engineer
Artificial Intelligence and Machine Learning
AWS Azure CI/CD GCP LSTM Machine Learning MLOps NetSuite Power BI Python Salesforce SAP Serverless SQL Tableau
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Samsara

Samsara

Samsara pioneers the Connected Operations Cloud, offering AI safety programs, real-time visibility, and integrations for industries to enhance efficiency, safety, and sustainability globally.

IT Services
1K-5K
Founded 2015
View All Jobs 346

Description

  • Define the end-to-end AI transformation roadmap for supply chain with the SVP of Operations and executive stakeholders.
  • Design, train, validate, and deploy ML models to production for demand forecasting, inventory optimization, supplier risk scoring, and cellular spend prediction.
  • Build predictive models for demand, lead times, and cellular spend across Samsara’s global supply network.
  • Create novel features from ERP, IoT, and third-party datasets and build pipelines and ETL jobs to support models and stakeholders.
  • Deliver production-grade code that supports both batch and real-time inference using MLOps best practices.
  • Partner cross-functionally with Product, Engineering, Procurement, and Finance to align on data needs, integrations, and change management.
  • Improve data infrastructure and analytics platforms to support real-time training, monitoring, and inference at scale.
  • Mentor junior scientists through code reviews and collaborative project work.
  • Lead experimentation, roadmap planning, modeling strategy, and scientific standards for the team.
  • 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.
  • Drive adoption of AI tools and insights-driven workflows across supply chain teams.
  • Hire, develop, and lead an inclusive and high-performing team.

Requirements

  • 8+ years of experience 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 a related technical field.
  • Expertise in statistical modeling and machine learning, including time series forecasting, optimization, anomaly detection, and causal inference.
  • Strong Python coding skills and fluency in SQL, with experience developing and deploying production ML systems.
  • Experience with MLOps practices, including automated testing, CI/CD, model versioning, monitoring, and performance tracking.
  • Experience building real-time inference pipelines and managing GPU/TPU resources for training at scale.
  • Familiarity with data visualization tools such as Tableau or Power BI and cloud platforms such as AWS, GCP, or Azure.
  • Strong problem-solving, critical thinking, and communication skills, with the ability to explain technical concepts to non-technical stakeholders.
  • Track record of collaborating cross-functionally and driving adoption of data-driven solutions.
  • Preferred: experience designing and validating experiments such as A/B tests and multi-armed bandits, and applying Bayesian methods for uncertainty quantification.
  • Preferred: advanced time-series modeling experience with tools such as Prophet, LSTMs, or Transformer-based approaches.
  • Preferred: experience reducing cloud/GPU spend through model compression or serverless architectures.
  • Preferred: experience deploying low-latency inference across multiple geographic regions with failover and disaster recovery.
  • Preferred: experience evaluating third-party ML platforms and contributing to or leveraging open-source projects.
  • Preferred: deep supply chain domain knowledge, including S&OP, IBP, safety stock, EOQ, ERP systems, and inventory optimization theory.

Benefits

  • Annual base salary of $170,170 to $257,400 USD.
  • Eligible for an initial RSU grant with no vesting cliff and ongoing refresh opportunities tied to performance.
  • Above-market total compensation, including base salary, performance-based bonus or variable pay, and equity for eligible roles.
  • Flexible, employee-led remote work model.
  • Comprehensive health plans.
  • Parental leave plans.
  • Professional development stipend.

Interested in this position?

Apply directly on the company website

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