Staff Machine Learning Engineer
Core
Lead the development of next-generation AI/ML systems for ETA, risk, anomaly detection, and supply chain intelligence, integrating Generative AI and agentic systems into core logistics workflows.
Role type
Staff Machine Learning Engineer (Supply Chain AI)
Builds
Production-grade ML systems, reusable Data Science platform primitives, and GenAI/agentic solutions for global logistics networks.
Domain
Logistics / Supply Chain / AI
Deliverable
production ML models
Required skills
Production-grade ML system design, Generative AI & LLM application development, advanced modeling (transformers, probabilistic, tree-based), MLOps & data platform fluency, distributed systems engineering, business impact translation, analytical rigor & diagnostics, data quality & signal awareness, modeling judgment & trade-offs, leadership & stakeholder influence
Preferred skills
Logistics/supply chain domain expertise, geospatial data & routing systems, anomaly detection & fraud modeling, internal platform building
Technologies
Python, SQL, Snowflake, Databricks, Spark, Airflow, Kafka, vector databases, RAG frameworks
Responsibilities
Lead end-to-end development of models for ETA, risk, anomaly, and fraud; Build reusable ML infrastructure (features, experimentation, deployment, monitoring); Lead GenAI & agentic systems (RAG, diagnostics, automation); Translate business problems into ML solutions; Drive experimentation & evaluation frameworks; Collaborate across engineering teams to build scalable systems
Seniority
Staff, hands-on IC with strategic scope
