Senior ML Engineer (Client Solutions)
Core
Build and deploy physics-informed ML systems directly inside client environments for energy, real estate, and logistics clients.
Role type
Senior ML Engineer (Client Solutions)
Builds
Production ML models, FastAPI services, and React dashboards for client data environments
Domain
Energy, Utilities, Commercial Real Estate, Logistics
Deliverable
production ML models
Required skills
Time-series forecasting and detection, Data engineering (pandas, SQL, DuckDB), Model validation (chronological splits, walk-forward), Python software engineering, Client-facing technical communication, FastAPI/React development, Docker/Cloud deployment
Preferred skills
LLM agentic workflows, Domain experience in Energy/Real Estate, Master's degree
Technologies
Python, SQL, Postgres, TimescaleDB, FastAPI, React, TypeScript, Docker, AWS, Azure
Responsibilities
Own full ML delivery lifecycle from data discovery to retraining, Build forecasting models resilient to data quality issues, Design systems distinguishing no prediction from wrong prediction, Ship usable product surfaces (APIs, dashboards), Define and monitor KPIs with clear attribution limits, Maintain client-facing engineering presence and feedback loops
Seniority
Senior, hands-on IC