---
title: 'Senior ML Engineer (Energy & Utilities) at AZX'
canonical: 'https://feeny.ai/job/senior-ml-engineer-energy-utilities-azx-seattle-dt5nq2aky62d'
type: 'job'
last_seen: '2026-09-10'
---

# Senior ML Engineer (Energy & Utilities) at AZX

- **Company:** AZX
- **Location:** Seattle, WA
- **Compensation:** $140k–$230k
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-08-31
- **Last confirmed live:** 2026-09-10
- **Apply:** https://jobs.ashbyhq.com/careers.azx.io/19109ff0-e6bb-4cf9-bedd-5510705a5b70

## Job description

## About AZX

Our mission is to accelerate positive impact in critical industries through AI transformation. We specialize in physics-informed ML and enterprise AI solutions that directly address climate and sustainability challenges. We’re growing quickly and already work with category-leaders in real estate (CBRE), energy (LevelTen Energy), logistics (Flexe) and utilities. We bootstrapped profitably for our first year and are now backed by leading investors focused on AI, climate and energy. We work on challenges in clean energy, decarbonization, climate risk, energy systems, and global economics. We’re building our company for long-term success and aim to create the ultimate place to work for those passionate about AI and making a positive impact.

About This Role: We are seeking a Senior ML Engineer that will build the AI models and underlying tools that power AZX's work with utility clients — reusable capabilities used across many client engagements. Underneath the models, you'll also build the infrastructure that makes them possible: a fast building-energy simulation engine, tools for reading real-time grid sensor data, and utilities for working with standardized building data formats — much of which we publish as open source, so some of the people using your work are outside engineers you'll never meet. Rather than being assigned to one client account, you'll build the capabilities that every client-facing team draws on, and you'll join a specific project when your tools meet real-world data and need to be adjusted based on what actually happens in the field.

Responsibilities:

- Own the reusable utility ML libraries — forecasting, disaggregation, demand response, detection, and asset health — each shipped with its own evaluation harness and documentation.
- Build capabilities once as tested libraries with validation harnesses, so client pods deploy proven components (like meter disaggregation or load forecasting with abstention and monitoring built in) instead of reinventing them per engagement.
- Own the simulation engine — Rust crates and Python bindings — including its validation methodology against the reference oracle and its performance, and use it to make city-scale building stock tractable through representative-archetype simulation.
- Own the grid-data toolkits: protocol codecs (IEEE C37.118-class), synthetic scenario generators, and verification utilities, including generating synthetic-but-believable meter data calibrated until domain experts can't tell.
- Build the planning and dispatch support behind demand-response programs, where acting on a wrong number carries real cost.
- Own the publish path — versioned crates and Python packages — shipped with the evidence (evals, benchmarks) attached.
- Own the feedback loop with client pods: track what the capability got wrong in the field, and turn that into what you build next.

Core Qualifications:

- 5+ years of shipping applied ML on real-world signals — forecasting, disaggregation, detection/classification on interval or sensor data, survival/reliability modeling, or an adjacent-industry equivalent
- Strong numerical and scientific computing skills: feature engineering from raw interval data, solver-level numerics when needed, and a healthy distrust of your own metrics.
- Python plus a systems language — the models and tooling are Python, the engine is Rust; depth in one, working ability in the other, and the appetite to close the gap (Rust is teachable here; modeling judgment isn't).
- Library craft: you build things other engineers consume — versioned, tested, documented, with an API you'd want to call yourself.
- Willingness to do your own data engineering — finding, cleaning, joining, and profiling inputs yourself rather than trusting a prepared dataset.
- Practical fluency in our core stack — Python 3.12+ (numpy, pandas/polars, scikit-learn, statsmodels), time-series feature engineering, forecasting/clustering libraries (sktime/statsforecast-class), and SQL/Postgres or TimescaleDB-class hypertables.
- Comfort picking up Rust (or a comparable systems language) via PyO3/maturin, and building evaluation harnesses and CI for scientific software.
- Willingness to ramp quickly on energy-domain vocabulary if you don't already have it
- Bachelor's Degree; Master's is a plus

Why AZX!

- Be part of a fast-growing, profitable, mission-driven company with industry-leading clients tackling the massive opportunity of AI transformation in critical industries.
- 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

Additional Information:

- Must be able to travel 2x/year for company summits
- Applicants must be currently authorized to work in the United States on a full-time basis.
- We are unable to sponsor or take over sponsorship of employment visas at this time.
- Please note that our interview process includes a written take-home assignment followed by a live two-hour technical session with our engineering team, so if that format isn't a good fit, we'd ask that you not apply
- Please only apply to a maximum of 2 roles at a time, any applicants who apply to more then 2 roles within a 6 month period will automatically be disqualified

Next Steps: If this job sounds like a great fit but you don’t check ALL of these qualification boxes, we’d still love to hear from you!

## About AZX

## Company Overview
- **One-liner**: AZX is a vertical AI platform and transformation partner that builds custom AI applications to accelerate positive impact in critical infrastructure industries like energy, utilities, real estate, and logistics.
- **Entity Type**: Private (Pre-Seed, $6 million raised)
- **Headquarters**: Seattle, Washington, United States (with a registered address in Bellevue, WA)
- **Founded**: 2024
- **Founders**: Aaron Goldfeder (CEO), Richard Evans (Chief Technologist), Michael Albrecht

## Core Business
- **Primary industry/industries**: AI Transformation for Critical Infrastructure (Energy, Utilities, Real Estate, Logistics)
- **Target customers**: B2B, Enterprise, and Mid-Market (category leaders in regulated and complex industries like power utilities, commercial real estate, and logistics)
- **Mission or purpose statement**: To accelerate positive impact in critical industries through AI transformation. The company is structured as a Public Benefit Corporation (PBC).

## Products & Services
- **AZX Platform (Vertical AI for Critical Infrastructure)**: A growing platform of reusable data, code, and models built from client engagements. It focuses on solving messy, unstructured data problems and brittle workflows that off-the-shelf tools fail to fix. The model is a hybrid of high-touch strategy consulting and custom engineering, with reusable components that compound over time.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Key Metric**: Total Funding — **$6 million** pre-Seed round (announced in 2025/2026). Revenue is reported to be **up 10x** since the prior year.
- **Notable Investors/Partners**:
    - **Investors**: AI2 Incubator, Ascend.vc, SFV, Founders' Co-op, Kompas, Powerhouse Ventures, Stepchange Ventures.
    - **Clients/Partners**: Puget Sound Energy, CBRE, Franklin Energy, Flexe, Trilliant.
- **Growth Signals**:
    - Headcount roughly **20** (full-time + contractors) and planning to **double** in the coming year.
    - Revenue growth of **10x** year-over-year.
    - Active hiring across engineering, GTM, and operations (10+ open roles).
    - LinkedIn followers: 656 (monthly growth of +10.8%).

## Competitive Advantages
- **Vertical Focus**: Deep domain expertise in energy, utilities, and real estate, differentiating from horizontal SaaS platforms like Palantir (which are often too expensive for mid-market) and large integrators like Accenture.
- **Hybrid Model**: Combines high-touch, forward-deployed strategy and engineering with a reusable platform, creating a compounding moat that makes each engagement faster and more valuable.
- **Founding Team**: Founders are seasoned entrepreneurs with prior exits (EnergySavvy acquired by Uplight; Meetingflow acquired in 2024) and deep ties to the energy industry.
- **Public Benefit Corporation**: Mission-driven structure attracts talent and clients aligned with climate and sustainability goals.

## Strategic Focus
- **Scale the team**: Aggressively hiring to double headcount (targeting ~40 people).
- **Platform acceleration**: Extracting reusable capabilities from client work to shorten future deployment cycles.
- **Deepen client relationships**: Expanding within existing accounts (Puget Sound Energy, CBRE) and acquiring new category leaders in critical infrastructure.
- **GTM expansion**: Hiring a Director/VP of GTM and Client Engagement Managers to formalize sales motions.

## Why Work Here
- **Culture**: Described as high-EQ, low-drama, positive impact, fun, and flexible. The team is small (~20 people) and mission-driven.
- **Remote/Hybrid**: Fully remote culture with a cluster of colleagues in Seattle. Twice-yearly immersive in-person summits.
- **Benefits**: Competitive base + bonus, healthcare with meaningful dependent coverage and HSA, flexible time off, stock equity, 401k. The company emphasizes that if you are driven by perks, you might be happier at big tech, but if you are motivated by impact and upside, this is a strong fit.
- **Engineering Culture**: Focus on "code over PowerPoint" and solving real-world problems. Roles include Senior Full Stack Engineer, Senior ML Engineer, and GTM AI Engineer.

## Sources
1. [azx.io - Careers Page](https://www.azx.io/careers)
2. [LinkedIn - AZX Company Page](https://www.linkedin.com/company/azxpbc)
3. [Ascend.vc - Investing in AZX](https://www.ascend.vc/blog/investing-in-azx)
4. [Kompas.vc - Why we invested in AZX](https://www.kompas.vc/news/why-we-invested-in-azx)
5. [Built In Seattle - AZX Profile](https://www.builtinseattle.com/company/azx)

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