Senior ML Engineer (Energy & Utilities)

Responsibilities

• Own reusable utility ML libraries for forecasting, disaggregation, demand response, detection, and asset health, including evaluation harnesses and documentation.
• Build tested, validated libraries so client teams can deploy proven components without recreating them for each engagement.
• Own the Rust-based simulation engine and Python bindings, including validation against a reference oracle, performance, and representative-archetype simulation at city scale.
• Build grid-data toolkits including protocol codecs, synthetic scenario generators, and verification utilities for realistic meter data.
• Develop planning and dispatch support for demand-response programs.
• Publish versioned crates and Python packages with evaluations and benchmarks attached.
• Track field failures with client teams and convert those findings into future capabilities.

Requirements

• At least 5 years of experience shipping applied ML on real-world signals such as forecasting, disaggregation, detection or classification, and survival or reliability modeling.
• Strong numerical and scientific computing skills, including feature engineering from raw interval data and solver-level numerics when needed.
• Strong Python skills plus working ability in a systems language; the role uses Python for models and tooling and Rust for the engine.
• Experience building versioned, tested, documented libraries with usable APIs for other engineers.
• Ability to find, clean, join, and profile data independently rather than relying only on prepared datasets.
• Practical fluency with Python, numerical and data libraries, time-series feature engineering, forecasting and clustering libraries, and SQL databases such as Postgres or TimescaleDB.
• Ability to work with Rust or a comparable systems language through PyO3 and maturin, and to build evaluation harnesses and CI for scientific software.
• Ability to learn energy-domain terminology quickly.
• Bachelor's degree required; master's degree is preferred.

Benefits

• Competitive early-stage startup compensation based on capabilities, experience, and location, plus bonus eligibility and equity.
• Health insurance with meaningful dependent coverage.
• Flexible paid time off.
• Fully remote culture with a cluster of teammates in Seattle.
• Travel twice per year for company summits.
• Applicants must be authorized to work full-time in the United States; visa sponsorship is unavailable.