Senior AI/ML Engineer - Supply Chain Optimization (Remote)

Samsara; New York (NY); Remote; USD 180,000 - 240,000; Full time

Benefits offered by this job

Equity compensation

Flexible remote work

Professional development stipend

Parental leave

Job summary

Samsara is hiring an experienced AI/ML Engineer to join its supply chain AI transformation. You will design and deploy ML models forecasting demand, inventory needs, and supplier risk using real‑time IoT signals and ERP data.

You’ll build end‑to‑end features, ensure MLOps practices, and collaborate with Product, Engineering, Procurement, and Finance to deliver measurable business impact.

Qualifications

• 8+ years in applied data science or ML, ideally in supply chain, operations, logistics, or manufacturing.
• Master's or PhD in Computer Science, Statistics, Data Science, EE, OR, or related field.
• Strong Python coding skills and fluency in SQL; production ML experience.
• Experience with MLOps, CI/CD, monitoring and model lifecycle management.

Responsibilities

• Define end-to-end AI transformation roadmap for supply chain with stakeholders.
• Design, train, validate, and deploy ML models to production with ROI impact.
• Build predictive models for demand, inventory, and supplier risk across the network.
• Create features from ERP, IoT, and third-party data; develop pipelines and ETL.
• Deliver production-grade code supporting batch and real-time inference.
• Mentor junior scientists and drive cross-functional adoption of data-driven workflows.

Skills

Python programming

SQL

ML time-series forecasting

MLOps

Production ML systems

Cross-functional collaboration

Data visualization tools

Education

Master's or PhD in CS / Statistics / Data Science

Tools

Tableau

Power BI

AWS

GCP

Azure

Job description

Samsara is hiring an experienced AI/ML Engineer to join its supply chain AI transformation. You will design and deploy ML models forecasting demand, inventory needs, and supplier risk using real‑time IoT signals and ERP data.

You’ll build end‑to‑end features, ensure MLOps practices, and collaborate with Product, Engineering, Procurement, and Finance to deliver measurable business impact.