Senior Applied ML Engineer ML4Sys
Databricks is a data and AI platform that lets organizations build analytics, AI agents, and applications on a unified, governed lakehouse.
Funding history
Investors
About Databricks
Data engineers, analysts, and AI teams use Databricks to process large datasets, build reliable pipelines, and train models on a single governed platform. Users can run SQL analytics, serve ML predictions in real time, and deploy AI agents grounded in enterprise data. Its open lakehouse architecture provides consistent security and governance across analytical and operational workloads.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will design, train, and deploy machine learning solutions that improve infrastructure efficiency and workload performance. You will build production ML pipelines, data-processing layers, model-serving components, and monitoring systems. You will also research and apply optimization techniques for distributed systems, cluster management, and query compilation.
Requirements
- Master's degree in Machine Learning, Data Science, or a related computational field
- Experience building, training, and deploying production machine learning models
- Familiarity with cloud computing, distributed systems, and data-processing frameworks
- Proficiency in Python, Scala, or Java
Responsibilities
- Drive scaling and efficiency through optimization techniques
- Design end-to-end ML4Sys solutions
- Define the roadmap for applied ML investments
- Architect, train, and deploy models that improve performance and cost efficiency
- Build ML pipelines, data-processing layers, model-serving components, and monitoring systems
- Research and implement modeling techniques for computer systems and distributed environments
Benefits
- Annual performance bonus eligibility
- Equity eligibility