Jobs · Engineering · California

Platform Engineer

Unlearn.AI · San Francisco, CA · 3 wk ago
HybridEngineering$50/hrFull-time

About the role

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.

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

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)

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