Applied AI Engineer
Databricks is a data and AI platform that lets organizations build analytics, AI agents, and applications on a unified, governed lakehouse.
Maintainer signals as of 9/25/2026
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 build agentic end-to-end systems and applied ML solutions. You will develop, deploy, and monitor ML and AI models, architect scalable training and serving infrastructure, work on forecasting techniques, and engage with engineering and product teams on applied ML investments.
Requirements
- 2–8 years of engineering experience in high-velocity, high-growth companies.
- Software engineering skills.
- Knowledge of testing and deployment principles.
Responsibilities
- Build agentic end-to-end systems.
- Build ML solutions for software engineers, ML engineers, data engineers, data scientists, and MLOps engineers.
- Own applied ML investments with engineering and product teams.
- Develop and deploy ML and AI models and systems.
- Architect and implement scalable ML infrastructure for model training and serving.
- Work on forecasting techniques.