Staff Machine Learning Engineer, CustomerLake (ML/LLM)

The impact you'll have:

• Evaluate ML and LLM approaches for CustomerLake's personalization use cases, push the models and algorithms forward, and continuously improve quality over time
• Go deep on how models behave in production: inspect individual traces, understand how the models reason, and tune and improve from there
• Build the platform and evaluation framework that let CustomerLake customers optimize for real business value such as purchases, retention, and product usage, not vanity metrics like email opens and clicks
• Push the team toward new directions and novel methods worth tackling, not just optimizing what already exists
• Partner closely with product management, engineering, and design to turn ambiguous customer problems into scalable, trustworthy solutions
• Set the technical foundation and best practices for our ML/AI personalization work as we grow this into several roles across our products over the next 1-2 years

What we look for:

• 10+ years of engineering experience, with a strong foundation across the full loop of shipping and improving ML/AI products
• Hands-on experience building and evaluating ML models and/or LLM systems for real product or business use cases; your understanding is practical, not purely academic, and you can make models work well inside a product
• Experience with personalization based on customer behavior (ideal) or transactions (acceptable), such as recommendations, targeting, churn, or lifetime-value modeling
• Proficiency in Python and modern ML frameworks (e.g., PyTorch), with hands-on experience in model evaluation and monitoring AI quality in production
• Familiarity with LLMs and generative AI, including techniques like retrieval-augmented generation (RAG), prompt design, fine-tuning, and evaluation
• A demonstrated product mindset, with the ability to translate ambiguous customer problems into scrappy MVPs and iterate quickly based on data and user feedback
• High ownership and bias for action in 0-to-1 environments: comfortable making pragmatic trade-offs, operating with incomplete information, and driving projects from idea through launch and adoption

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.