# ML/AI - Supply Chain

**Company**: Samsara
**Location**: Remote - US
**Work arrangement**: remote
**Experience**: senior
**Job type**: full-time
**Salary**: $178,640-$319,000 USD
**Category**: Data Science
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/samsara/jobs/8359956?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/job/ml-ai-supply-chain-7aa6dd2b-b6f/

## Description

Samsara is building an AI/ML team inside its Operations team to make its supply chain AI native. You would be one of its first AI/ML engineers. You will design, develop, and deploy advanced machine learning and statistical models that optimize the global supply chain.

Responsibilities:

- Define the end-to-end AI transformation roadmap for supply chain alongside the Senior Director of Supply Chain AI Transformation

- Design, train, validate, and deploy ML models to production (demand forecasting, inventory optimization, supplier risk scoring, cellular spend prediction, HW cash flow)

- Build predictive models to forecast demand, inventory, lead times, and spend across Samsara's global supply network

- Create novel features using large-scale ERP, IoT, and third-party datasets

- 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

- Drive enhancements to the data infrastructure and analytics platform

- Mentor junior scientists through code reviews and collaborative project work

- Identify gaps in data, tools, and processes,and lead initiatives to close them

Requirements:

- 8+ years 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 related technical field

- Expert in statistical modeling and ML: time series forecasting, optimization, anomaly detection, causal inference

- Strong Python coding skills and fluency in SQL

- Proficiency in MLOps practices: automated testing, CI/CD, model versioning, monitoring, performance tracking

Nice to have:

- 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

For more fresh new jobs, check out [yubhub.co](https://yubhub.co/).

## Skills

### Required
- Python
- SQL
- MLOps
- statistical modeling
- machine learning
- data science

### Nice to have
- Bayesian methods
- Prophet
- LSTMs
- Transformer-based
- model compression

---

Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/samsara/jobs/8359956?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)