Platform Engineer — Data & ML Infra for Health AI

RiseMe; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Function Health is seeking a Platform Engineer-level Data Infrastructure engineer to shape the data and ML pipeline stack. You will own event tracking, data contracts, and scalable processing in a lakehouse with Databricks, ensuring robust CI/CD and deployability for product analytics and ML features.

You will collaborate across product and engineering teams to design schemas, promote governance, and harden the platform for reliable decision-making in health AI applications.

Qualifications

• Built internal platform or infrastructure that engineers adopted.
• Operated production data or ML systems, on call for them, and fixed them under pressure.
• Strong Python and SQL. Comfortable in a lakehouse – we use Databricks; Snowflake or BigQuery translates fine.
• Designed interfaces and schemas that other teams depend on, then evolved them without breaking those teams.
• Thought hard about testing and CI for data or ML, where correctness is statistical and the failure is often silent.
• 1-4 years of engineering experience gets you here, but we care about what you've built, not the number.

Responsibilities

• Tracking infrastructure: the event pipeline behind product analytics, experimentation, and feature gates.
• Data processing infrastructure: Bronze → Silver → Gold, contract tests, backfills with safe operators.
• ML infrastructure: feature computation, training/eval pipelines, model output integration with product.
• Self-service progression: templates, local dev, policy-as-code for PHI, and progressive gates.

Skills

Python

SQL

Databricks

Data modeling

CI/CD for data/ML

Data quality testing

API design

Tools

Databricks

Kafka

Airflow

Terraform

Job description

Function Health is seeking a Platform Engineer-level Data Infrastructure engineer to shape the data and ML pipeline stack. You will own event tracking, data contracts, and scalable processing in a lakehouse with Databricks, ensuring robust CI/CD and deployability for product analytics and ML features.

You will collaborate across product and engineering teams to design schemas, promote governance, and harden the platform for reliable decision-making in health AI applications.