Senior ML Engineer (Energy & Utilities)
Core
Building reusable utility ML libraries and a Rust-based simulation engine for energy forecasting, demand response, and asset health at city scale.
Role type
Senior IC machine-learning engineer (energy systems)
Builds
Versioned Rust/Python libraries, simulation engines, grid-data toolkits, and planning/dispatch support for demand-response programs.
Domain
Energy & Utilities / Power Grids
Deliverable
production ML models | infrastructure
Required skills
Applied ML on real-world signals (forecasting, disaggregation, detection, survival modeling), numerical and scientific computing, feature engineering from raw interval data, solver-level numerics, Python, Rust (PyO3, maturin), time-series feature engineering, clustering, SQL (Postgres, TimescaleDB), building tested/documented libraries with usable APIs, data profiling and cleaning, CI/CD for scientific software.
Preferred skills
Master's degree, energy-domain terminology knowledge.
Technologies
Rust, Python, PyO3, maturin, Postgres, TimescaleDB
Responsibilities
Own reusable utility ML libraries for forecasting, disaggregation, demand response, detection, and asset health; Build tested, validated libraries for client deployment; Own the Rust-based simulation engine and Python bindings; Build grid-data toolkits including protocol codecs and synthetic scenario generators; Develop planning and dispatch support for demand-response programs; Publish versioned crates and Python packages with evaluations and benchmarks; Track field failures and convert findings into future capabilities.
Seniority
Senior, hands-on IC