Platform Engineer

Unlearn•San Francisco, CA

About The Position

We are seeking a high-caliber Platform Engineer to join our mission. At our core, we believe that world-class AI and software is only as good as the platform it runs on. We are looking for a software engineer who views MLOps and infrastructure as a software problem. In this role, you will build the Clinical AI Platform for our science and product teams, creating internal tools, automated workflows, data tools, pipelines, and infrastructure that allow out teams to deliver value to our customers. You will be the architect of a resilient, high-performance ecosystem designed specifically for the unique demands of clinical data and high-compute AI workloads.

Requirements

5+ years of experience building software platforms, data engineering, or MLOps initiatives
Track record of successfully delivering complex infrastructure projects and driving technical decisions
Strong communication skills with experience presenting technical concepts to leadership and stakeholders
Experience with cloud platforms (AWS; Azure and GCP a plus), containerization (Docker, Kubernetes), and infrastructure-as-code tools (Terraform)
Proven ability to architect and implement MLOps solutions in production environments
Strong programming, scripting, and automation skills
Familiarity with Data Engineering tools (dbt) and pipelines (Dagster) in a plus
Familiarity with compliance requirements in regulated industries, such as healthcare or life sciences is a plus

Nice To Haves

Experience with MLFlow and Databricks
AI/ML Awareness: Familiarity with the unique infrastructure needs of AI (e.g., NVIDIA Triton, Slurm, or Ray)

Responsibilities

Lead and execute Data Platform and MLOps initiatives, driving technical decisions and ensuring alignment with business priorities and timelines
Develop and implement infrastructure roadmaps, effectively communicating progress, challenges, and resource needs to leadership
Architect and implement scalable platform solutions that support both internal development and production deployments
Establish and maintain infrastructure best practices that balance reliability, efficiency, security, and compliance requirements
Partner with product engineers and scientists to understand their data and platform needs and translate them into actionable solutions
Ensure infrastructure decisions and implementations align with security best practices and regulatory requirements