Senior ML Engineer – Client Solutions

🔥 0 minutes ago

☕ Washington – Remote

☕ Washington – Remote

💵 $140k - $230k / 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 ML systems directly inside client environments, from client data discovery through scheduled production deployment • Own the full ML delivery lifecycle: data discovery and cleaning, modeling, evaluation, deployment, scheduling, monitoring, and retraining policy • Build forecasting and detection models resilient to late feeds, revised rows, and missing labels • Backtest and evaluate models, defending precision/recall tradeoffs to operational stakeholders • Design systems that distinguish “no prediction” from “wrong prediction” for end users • Ship usable product surfaces such as FastAPI services, React interfaces, and scheduled jobs • Establish baselines and KPIs before deployment, instrument monitoring, and deliver post-deployment readouts with attribution limits • Serve as the client-facing engineering representative through discovery, working sessions, demos, and collaboration with client IT/data teams • Feed client data shapes and failure modes back to the platform team • Contribute across DevOps, infrastructure, front-end, and back-end engineering as part of a small team

🎯 Requirements

• 5+ years of shipping applied machine learning to production • Experience with forecasting, detection/classification on time series, survival/reliability modeling, or optimization • Strong data engineering skills, including finding, cleaning, joining, and profiling data at awkward scale • Chronological splits, walk-forward validation, and as-of correctness • Python, SQL, tests, Docker, a scheduler, an API or app surface, and monitoring • Client-facing capability, including discovery, demos, and pushing back on incorrect requests • Judgment about when ML is the wrong tool • Python 3.12+ with pandas/polars/DuckDB, scikit-learn, statsmodels, and gradient boosting • SQL/Postgres, with TimescaleDB/PostGIS for grid work • Time-series feature engineering and validation • FastAPI and enough React/TypeScript to expose results • Docker and basic Azure/AWS cloud tooling • Working fluency with LLMs for extraction and retrieval • Bachelor's Degree required; Master's is a plus • Currently authorized to work full-time in the United States • Domain experience in Energy, Utilities, Infrastructure, and Commercial Real Estate is a plus • Ability to travel 2x/year for company summits • Written take-home assignment followed by a live two-hour technical session • Maximum of 2 role applications at a time; more than 2 roles within 6 months results in 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