Remote Senior ML Engineer — Production AI for Climate

careers.azx.io; Seattle (WA); On-site; USD 170,000 - 210,000; Full time

Benefits offered by this job

Health insurance

Equity

Flexible PTO

Bonus eligibility

Fully remote with Seattle cluster

Job summary

AZX is seeking an ML Engineer to build ML systems directly inside client environments. You’ll start with the client’s data, then deploy a model on a schedule within their environment, wearing many hats across DevOps, infrastructure, and frontend/backend.

You’ll own end-to-end delivery, including data discovery, modeling, evaluation, deployment, monitoring, and retraining policies, while communicating tradeoffs and results to stakeholders.

Qualifications

• 5+ years of shipping applied ML to production with forecasting or detection.
• Strong data engineering ability to find, clean, join data at scale.
• Rigorous validation: chronological splits and walk-forward validation.
• Ship real systems: Python, SQL, tests, Docker, an API or app surface, monitoring.
• Client-facing capability: run discovery, demos, and push back when needed.
• Judgment about when ML is the right tool for a client need.
• Fluency with core stack: Python 3.12+, pandas/polars, scikit-learn, time-series tools.
• Experience with FastAPI and React/TypeScript, and deploying with cloud tooling.
• Exposure to LLMs for agentic edges of client work.
• Bachelor's Degree; Master's is a Plus
• Domain experience in Energy/Utilities/Infrastructure/ CRE is a plus

Responsibilities

• Own the full ML delivery lifecycle: data discovery, modeling, deployment, scheduling, monitoring, retraining.
• Build forecasting and detection models resilient to late feeds and data issues.
• Backtest and evaluate models, defending precision/recall tradeoffs.
• Design systems that distinguish no prediction from wrong prediction for end users.
• Ship usable product: FastAPI service, React surface, scheduled jobs.
• Define baselines and KPIs; instrument and report post-deployment results.
• Maintain client-facing engineering presence with client data teams and demos.

Skills

ML in production

Data engineering

Validation discipline

Software engineering

Client-facing

ML judgment

Core stack Python

LLMs exposure

Education

Bachelor's Degree

Master's is a Plus

Tools

Docker

FastAPI

React

TypeScript

Python

SQL

Postgres

TimescaleDB

Azure/AWS

Job description

AZX is seeking an ML Engineer to build ML systems directly inside client environments. You’ll start with the client’s data, then deploy a model on a schedule within their environment, wearing many hats across DevOps, infrastructure, and frontend/backend.

You’ll own end-to-end delivery, including data discovery, modeling, evaluation, deployment, monitoring, and retraining policies, while communicating tradeoffs and results to stakeholders.