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Senior Applied ML Engineer - ML4Sys

Databricks· Engineering
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San Francisco, California$166k - $210.3kFull-timePosted 2mo ago

About the role

Senior Applied ML Engineer on the Applied AI team at Databricks, working on machine learning, scheduling, and optimization to maximize infrastructure efficiency and performance across the full stack from cluster management to query compilation.

Responsibilities

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

Qualifications

  • Background in Computer Science and Master's degree in Machine Learning, Data Science, or related computational field (AI, Bioinformatics, EE, Physics, etc).
  • Strong experience building, training, and deploying ML models in production.
  • Practical familiarity with cloud computing, distributed systems, and modern data processing frameworks.
  • Proficiency in Python, Scala, or Java.

Skills

Required:Machine learning model developmentCloud computing and distributed systemsProgramming languages
Last updated Sep 10, 2026. Interested? Apply on the company site.

About Databricks

Leading Data and AI Platform for Enterprises

Databricks offers a unified platform for data, analytics and AI. Build better AI with a data-centric approach. Simplify ETL, data warehousing, governance and AI on the Data Intelligence Platform.

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