ML Engineer (AI-Native Systems & Forecasting)
Core
Design, build, and deploy production-grade ML systems for demand forecasting, labor allocation intelligence, and LLM-powered workflows to optimize workforce infrastructure.
Role type
Senior Machine Learning Engineer (AI-Native Systems & Forecasting)
Builds
AI-native workforce infrastructure including demand forecasts, allocation systems, and a persistent labor graph
Domain
Labor market optimization, workforce infrastructure, AI systems
Deliverable
production ML models
Required skills
production ML system design, full ML lifecycle ownership, data ingestion and pipeline architecture, LLM system development (RAG, prompt design), statistical experimentation, model monitoring and drift detection, A/B testing design
Preferred skills
time-series forecasting, demand modeling, labor/logistics marketplace systems, custom model fine-tuning, ML team mentoring
Technologies
RAG pipelines, feature stores, Airflow, dbt
Responsibilities
Design and deploy ML systems for forecasting and optimization; own data ingestion, feature engineering, training, and deployment; remediate inconsistent datasets; build LLM-native systems; implement continuous model evaluation and monitoring; run statistical experiments; translate model insights for stakeholders
Seniority
Senior, hands-on IC with architectural influence