As a Senior Applied ML Engineer on the Applied AI team at Databricks, you will leverage machine learning and optimization algorithms to enhance the efficiency of our infrastructure. Your role will involve working across the entire stack, from cluster management to query compilation. You will tackle complex engineering challenges to deliver optimized workloads for our customers. This position requires collaboration with engineering and product leaders to shape the strategy for applied ML investments.

• Master's degree in Machine Learning, Data Science, or a related computational field.
• Strong background in building, training, and deploying machine learning models in production.
• Practical familiarity with cloud computing, distributed systems, and modern data processing frameworks.
• Proficiency in Python, Scala, or Java.

• Drive the scaling and efficiency of Databricks serverless compute products through advanced optimization techniques.
• Design end-to-end ML4Sys solutions from the ground up within a lean team of domain experts.
• Define the roadmap for applied ML investments by collaborating with engineering and product leaders.
• Architect, train, and deploy state-of-the-art models that improve product performance and cost efficiency.
• Build robust ML pipelines, data processing layers, model serving components, and production monitoring systems.
• Research and implement novel modeling techniques tailored specifically to computer systems and distributed environments.