Staff Machine Learning Platform Engineer

3 days ago

H1B Sponsor

Base Salary

$247k - $339k/yr

Responsibilities

Design and operate ML infrastructure, including workspaces, clusters, jobs, and workflows.
Productionize ML workloads using Spark, Delta Lake, MLflow, and Databricks Workflows.
Enable data scientists to advance models from notebooks to production.
Implement Unity Catalog for data governance, lineage, access control, and secure multi-tenant usage.
Build ML CI/CD pipelines using Terraform and Git-based workflows such as GitHub Actions.
Optimize performance, reliability, and cost across training and inference workloads.
Configure IAM and RBAC for sensitive datasets.
Establish observability for data quality, model performance, and platform health.
Build and maintain ML platform technical documentation.

At least 8 years of experience building production ML or data platforms.
A degree in Computer Science, Engineering, Statistics, or a related technical field, preferably at graduate level.
Strong hands-on expertise with Databricks, Spark, Delta Lake, and MLflow.
Proficiency in Python and SQL, with an understanding of distributed systems concepts.
Experience with cloud platforms and infrastructure-as-code.
Understanding of MLOps practices including CI/CD, monitoring, reproducibility, and security.
Experience supporting multiple ML teams in a shared platform environment.
Demonstrated ownership of orphaned problems and willingness to learn missing knowledge to complete the work.

Base pay range of $246,500 to $339,000 per year for San Francisco, plus equity and comprehensive benefits.
Hybrid employees work in the office three days per week—Tuesdays, Thursdays, and one flex day—and may work remotely for up to four weeks per year.
Access to enterprise AI tools and opportunities for professional growth.
Equal employment opportunities and reasonable accommodations throughout the hiring process.

1,001-5,000 employees

Faire is a wholesale technology platform empowering brands and retailers to strengthen the unique character of local communities.