Staff ML Infrastructure Engineer
$250,000 + 600K equity
Series E Tech
San Francisco hybrid 3 days
About the Team:
My client's ML Infrastructure team is responsible for building and maintaining the scalable and reliable infrastructure that supports their machine learning models.
Job Description:
We are seeking an experienced Staff ML Infrastructure Engineer to lead the design and implementation of our machine learning infrastructure. As a Staff ML Infrastructure Engineer, you will be responsible for architecting and building the infrastructure that supports our machine learning models, including Kubernetes clusters, big data tooling, and workflow orchestration. You will also lead a team of engineers and collaborate with other stakeholders to drive the vision and strategy for our ML infrastructure.
Requirements:
- 7+ years of experience in building and maintaining scalable infrastructure
- Deep experience with Kubernetes, big data tooling (e.g. Spark, Snowflake), and workflow orchestration
- Background in DevOps practices and Python development
- Strong understanding of ML concepts and ability to work with large-scale data
- Experience leading a team of engineers and driving technical vision and strategy
Nice to Have:
- Experience with GPU support in Kubernetes
- Knowledge of Iceberg and Spark as the engine for the feature store
- Familiarity with CI/CD tools and workflow orchestration engines
