Senior ML Engineer – Energy & Utilities

🔥 0 minutes ago

☕ Washington – Remote

☕ Washington – Remote

💵 $140k - $225k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 2%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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AZX

WebsiteLinkedInAll Job Openings

1 - 10 employees

Founded 2024

💼 Consulting

📦 Logistics

🏗️ Construction

Consulting • Logistics • Construction

AZX is a public benefit corporation delivering AI solutions specifically tailored for the energy, real estate, and supply chain industries. They focus on solving client problems expediently by leveraging innovative strategies and engineering AI-enabled solutions that provide measurable results. With a mission-driven approach, AZX emphasizes creating impact in both organizational efficiency and environmental sustainability.

📋 Description

• Build AI models and underlying reusable tools for utility clients • Own reusable utility ML libraries for forecasting, disaggregation, demand response, detection, and asset health • Ship each library with evaluation harnesses and documentation • Build tested libraries with validation harnesses for client pods • Own the building-energy simulation engine, including Rust crates and Python bindings • Validate the simulation engine against the reference oracle and maintain its performance • Use representative-archetype simulation to make city-scale building stock tractable • Own grid-data toolkits, including protocol codecs, synthetic scenario generators, and verification utilities • Generate synthetic-but-believable meter data calibrated with domain experts • Build planning and dispatch support for demand-response programs • Own the publish path for versioned crates and Python packages with evaluations and benchmarks • Track capability failures in the field with client pods and turn feedback into future development • Join specific client projects when tools encounter real-world data and require adjustment • Publish much of the work as open source

🎯 Requirements

• 5+ years of shipping applied ML on real-world signals • Strong numerical and scientific computing skills • Python plus a systems language; working ability in Python and Rust or comparable systems language • Library craft: versioned, tested, documented libraries with usable APIs • Willingness to do your own data engineering • Python 3.12+ with numpy, pandas/polars, scikit-learn, and statsmodels • Time-series feature engineering • Forecasting/clustering libraries such as sktime/statsforecast-class • SQL/Postgres or TimescaleDB-class hypertables • Comfort picking up Rust via PyO3/maturin • Experience building evaluation harnesses and CI for scientific software • Willingness to ramp quickly on energy-domain vocabulary • Bachelor's Degree; Master's is a plus • Must be currently authorized to work in the United States on a full-time basis • Unable to sponsor or take over sponsorship of employment visas • Must complete a written take-home assignment followed by a live two-hour technical session • Applicants may apply to a maximum of 2 roles at a time; applying to more than 2 roles within 6 months results in automatic disqualification

🏖️ Benefits

• Competitive early-stage startup compensation (based on capabilities, experience, and location) • Bonus eligibility • Health insurance with meaningful coverage for dependents • Flexible paid time off • Equity • Fully remote culture with a cluster of teammates in Seattle • Company summits 2x/year