Databricks
Senior Applied ML Engineer - ML4Sys
$166K–$210K
San Francisco, California · Senior · Full-time · Posted Aug 3, 2026
- Experience
- Preferred: 4+ years of machine learning engineering experience in a high-velocity, high-growth environment.
- Education
- Background in Computer Science and a master's degree in Machine Learning, Data Science, or a related computational field; PhD preferred.
About the job
Applies machine learning, scheduling, and optimization to improve the efficiency, performance, and cost of Databricks infrastructure, from cluster management to query compilation.
What you'll do
- Design, train, deploy, and monitor ML solutions that improve product performance and cost efficiency.
- Build ML pipelines, data processing layers, and model-serving components for serverless compute.
- Research optimization methods and help shape the roadmap for applied ML investments.
What they ask for
- Background in Computer Science and a master's degree in Machine Learning, Data Science, or a related computational field.
- Strong background 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.
Nice to have
- PhD in AI, Data Science, or a related technical discipline.
- Experience in ML engineering, computer systems or cloud infrastructure optimization, or sequential decision-making optimization methods.
Pay
$166,000 — $210,250 USD (salary range)
Tools
Python, Scala, Java
AI focus
Build and deploy production ML models and infrastructure to optimize distributed systems, serverless compute, performance, and cost.
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