Senior Machine Learning Engineer – Client Solutions

About the role

AZX is looking for a Senior Machine Learning Engineer to deliver end‑to‑end ML solutions inside client environments. You will work directly with client data, build robust forecasting and detection models, and ensure they run reliably on schedule.

Key responsibilities

• Own the full ML delivery lifecycle: data discovery, cleaning, modeling, evaluation, deployment, scheduling, monitoring, and retraining.
• Build forecasting and detection models that tolerate real‑world data quality issues such as late feeds and missing labels.
• Design systems that differentiate “no prediction” from “wrong prediction” for clear user feedback.
• Ship usable product components – FastAPI services, React front‑ends, scheduled jobs, or similar.
• Define baselines and KPIs, instrument monitoring, and provide post‑deployment readouts with clear attribution.

Required profile

• 5+ years shipping applied machine‑learning models to production, especially time‑series forecasting, detection, or optimization.
• Strong data‑engineering ability to find, clean, join, and profile data at scale without a dedicated data team.
• Rigorous validation discipline using chronological splits, walk‑forward validation, and careful metric scrutiny.
• Experience communicating with clients, leading discovery sessions, demos, and pushing back on unrealistic requests.

Required skills

• Python 3.12+ (pandas, polars, DuckDB, scikit‑learn, statsmodels, gradient‑boosting libraries)
• SQL / PostgreSQL (including TimescaleDB, PostGIS)
• Docker, FastAPI, React/TypeScript for building and exposing model services
• Scheduler tools, monitoring, and basic cloud tooling (Azure or AWS)
• Time‑series feature engineering and validation techniques

What we offer

• Competitive early‑stage startup compensation with bonus eligibility
• Health insurance with meaningful coverage for dependents
• Flexible paid time off
• Equity participation
• Fully remote culture with occasional Seattle‑based team gatherings (travel 2× /year)