Founding ML Platform Engineer, Energy Intelligence

United States Digital Space LLC; San Francisco (CA); Hybrid; USD 180,000 - 280,000; Full time

Benefits offered by this job

Equity

Job summary

Energy Intelligence in San Francisco is seeking a founding ML Platform Engineer to design and own the core data and ML infrastructure that forecasts load and market prices. You will own the spine: ISO/RTO market feeds, weather and plant telemetry through a feature store, serving, drift detection and the model gateway.

Python, SQL, Airflow, containers and IaC are part of the stack. 5+ years on production data and ML platforms; energy background welcome, not required.

Qualifications

• Python, SQL, Airflow, containers and IaC used in production ML platforms.
• 5+ years on production data and ML platforms; energy background welcome, not required.

Responsibilities

• Own the spine: market feeds, feature store, drift detection and the model gateway.

Skills

Python

SQL

Airflow

Containers

IaC

Tools

Docker

Kubernetes

Job description

the company | Founding ML Platform Engineer, Energy Intelligence | San Francisco | HYBRID | Full-time | equity

We deliver multi-gigawatt power to AI data centers, and this is the founding hire on the team that forecasts load and market prices. You own the whole spine: ISO/RTO market feeds, weather and plant telemetry through feature store, serving, drift detection and the model gateway.

Not a scale problem — the data is rich, not petabyte. Feeds land late and get revised after the fact without ever throwing an error, so the failure mode is a price series quietly wrong for three weeks behind a forecast that looks fine. The work is trust infrastructure: lineage, freshness SLAs, point-in-time correctness, eval gates that can block a model.

Python, SQL, Airflow, containers, IaC. 5+ years on production data and ML platforms; energy background welcome, not required.