Applied AI Engineer

About the role

Databricks is hiring an Applied AI Engineer to help its customers build and deploy large-scale machine learning solutions such as personalized recommendations, fraud detection, dynamic pricing and forecasting, using Databricks' agents and harnesses. The engineer works on Genie Code, an agent and ML exoskeleton that authors, trains and deploys models, monitors them and helps self-heal production ML. The role reports to a Principal Software Engineer.

Key responsibilities

• Build agentic end-to-end systems in a small, highly international team in a flat and agile organization.
• Develop solutions for software engineers, ML engineers, data engineers, data scientists and MLOps engineers.
• Engage with engineering and product teams across the company to own the applied ML investment.
• Drive the development and deployment of state-of-the-art ML/AI models and systems that improve Databricks' products, infrastructure and services.
• Architect and implement robust, scalable ML infrastructure, including model training and serving components.
• Work on novel forecasting techniques.
• Possibility to present at conferences and contribute to open source projects.

Required profile

• 2-8 years of engineering experience in high-velocity, high-growth companies.
• Infrastructure and system engineers with no ML background who are willing to grow personally are welcome to apply.
• Experience developing AI/ML systems at scale in production and a strong track record of ML modeling beyond standard libraries is a plus.

Required skills

• Strong software engineering skills and familiarity with testing and deployment principles.
• Nice to have: experience deploying, scaling and monitoring models in production, and understanding of the infrastructure challenges of training and serving predictions in Tier 0 environments.