Jobs · Engineering · California

Staff Machine Learning Platform Engineer

Ladders · San Francisco, CA · 3 wk ago
On-siteEngineering$247k–$339k/yrFull-time

Location: San Francisco, CA – US based candidates only, no visa sponsorship available.

About the role

This role will lead technical work focused on cloud-enabled scalability, reliability, and delivery excellence. You will work across engineering, product, operations, and business stakeholders to translate complex requirements into practical technology solutions. The position offers the opportunity to influence architecture, execution quality, and the technology capabilities that enable long-term growth within a Business Services environment.

Responsibilities

  • Design and operate ML infrastructure, including workspaces and workflows
  • Productionize ML workloads using tools like Spark and Delta Lake
  • Teach data scientists to utilize the ML platform for model development
  • Implement Unity Catalog for data governance and access control
  • Build CI/CD pipelines for ML with Terraform and Git workflows
  • Optimize performance and cost for training and inference workloads
  • Establish observability for data quality and model performance

Qualifications

  • 8+ years of experience in building production ML or data platforms
  • Graduate degree in Computer Science, Engineering, Statistics, or related field preferred
  • Hands-on expertise with Databricks, Spark, Delta Lake, and MLflow
  • Proficient in Python, SQL, and distributed systems concepts
  • Experience with cloud platforms and infrastructure-as-code
  • Solid understanding of MLOps best practices
  • Experience in supporting multiple ML teams in a shared platform environment

Pay

$246,500 – $339,000 annually

Benefits

  • Flexible hybrid work model with remote work options
  • Opportunity to work with a team focused on empowering entrepreneurs
  • Supportive environment for experimentation and innovation
  • Engagement in a mission-driven company that values community growth
  • Access to cutting-edge technology and data to drive impact

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