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)