Senior ML Engineer – Client Solutions
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Job Description
Senior ML Engineer delivering production forecasting and detection systems for AZX’s climate and sustainability clients. Building data pipelines, APIs, monitoring, and client-environment deployments.
Responsibilities:
- 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
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