Senior ML Engineer (Client Solutions)
AZX · Remote · United States ·
COMPENSATION
$140k – $230k
Listed on the employer's job board (Ashby)
- Senior ML Engineer
- Fully remote (US)
- Python + SQL
- Client-facing role
- No visa sponsorship
You will design and implement machine learning systems directly inside client infrastructure, addressing challenges in clean energy, decarbonization, and climate risk. As the primary engineering contact, you will handle data discovery, model building, and deployment while collaborating with client IT teams.
The position requires strong software engineering skills to ship usable products, including APIs and lightweight front-end interfaces. You will ensure models are robust against real-world data issues and maintain rigorous validation standards throughout the delivery process.
What you'll do
- Own the full ML lifecycle from data cleaning to deployment and monitoring
- Build forecasting and detection models resilient to poor data quality
- Design systems that clearly distinguish missing predictions from incorrect ones
- Ship usable product components like FastAPI services or React interfaces
- Define baselines and KPIs with clients before deploying models
- Maintain client relationships through discovery sessions and technical demos
- Provide feedback to the platform team based on client-side failure modes
What you'll need
- 5+ years of experience shipping applied machine learning to production
- Strong data engineering skills for cleaning and profiling data at scale
- Proficiency in Python, SQL, Docker, and basic cloud tooling (AWS/Azure)
- Experience with chronological splits and walk-forward validation techniques
- Ability to build API surfaces and lightweight front-end interfaces
- Strong communication skills for leading demos and managing client expectations
- Judgment to identify when machine learning is not the appropriate solution
- Must be authorized to work in the United States full-time
Nice to have
- Master’s degree in a relevant field
- Domain experience in energy, utilities, or commercial real estate
- Practical experience using LLMs for extraction or retrieval tasks
Stack
- Python
- SQL
- Postgres
- TimescaleDB
- PostGIS
- pandas
- polars
- DuckDB
- scikit-learn
- statsmodels
- FastAPI
- React
- TypeScript
- Docker
- AWS
- Azure
How you'll work
- Fully remote culture with team cluster in Seattle
- Must be able to travel twice a year for company summits
- Applicants must be authorized to work in the US
What you get
- Competitive early-stage startup compensation
- Bonus eligibility
- Health insurance with coverage for dependents
- Flexible paid time off
- Equity package
Hiring process
- Written take-home assignment
- Live two-hour technical session with engineering team
- Limit of two active applications per candidate at any time