Senior Applied ML Engineer - ML4Sys
Core
Build ML4Sys solutions using machine learning, scheduling, and optimization algorithms to maximize the efficiency and performance of Databricks infrastructure from cluster management to query compilation.
Role type
Senior Applied ML Engineer (ML4Sys)
Builds
End-to-end ML4Sys solutions, serverless compute products, and optimized workloads for Databricks customers.
Domain
Cloud infrastructure, distributed systems, and data processing frameworks.
Deliverable
production ML models
Required skills
Machine learning model development, cloud computing, distributed systems, Python, Scala, Java
Preferred skills
PhD in AI/Data Science, operations research, optimization algorithms, large-scale distributed systems optimization
Technologies
Apache Spark, Delta Lake, MLflow, cloud computing platforms
Responsibilities
Design end-to-end ML4Sys solutions, define roadmap for applied ML investments, architect and deploy state-of-the-art models, build robust ML pipelines and monitoring systems, research novel modeling techniques for computer systems
Seniority
Senior, hands-on IC
