Staff Machine Learning Engineer, CustomerLake

About the role

Join a foundational team in our New York City office to build CustomerLake, a new Customer Data Platform designed to bring enterprise-grade AI and machine learning personalization to Databricks users. You will operate in a startup-like environment to deliver advanced modeling capabilities to companies that lack dedicated in-house data science teams.

Key facts

What you'll do

• Research and implement ML and LLM strategies for personalization, focusing on continuous quality improvement.
• Analyze model behavior in production by inspecting traces and reasoning patterns to refine performance.
• Develop evaluation frameworks that prioritize business outcomes like retention, purchase conversion, and product usage over vanity metrics.
• Drive technical innovation by proposing and testing novel methods rather than merely optimizing existing workflows.
• Collaborate with product, design, and engineering teams to transform complex customer requirements into scalable, reliable products.
• Establish technical standards and best practices for personalization, helping to scale the team over the next 1-2 years.

Requirements

• 10+ years of engineering experience with a proven track record of shipping and refining ML/AI products.
• Practical experience building and evaluating models or LLM systems for real-world business applications.
• Background in personalization using behavioral or transactional data, such as lifetime-value modeling, churn prediction, or recommendation systems.
• Proficiency in Python and modern ML frameworks like PyTorch, including production-level monitoring and evaluation.
• Knowledge of generative AI and LLM techniques, including RAG, fine-tuning, prompt design, and evaluation.
• Strong product intuition with the ability to build MVPs and iterate based on user feedback.
• Ability to thrive in 0-to-1 environments, manage trade-offs, and drive projects from concept to adoption.

Nice to have

• Experience in martech, specifically regarding business or go-to-market analytical use cases.
• Academic or research experience focused on developing novel methodologies.

Skills & tools

• Python
• PyTorch
• LLMs
• RAG
• Fine-tuning
• ML Model Evaluation
• Production Monitoring

Practical notes

• Compensation includes eligibility for annual performance bonuses and equity.
• The company may require a U.S. government license for access to export-controlled technology or source code; the company reserves the right to decline applicants based on this requirement.
• Databricks is an equal opportunity employer committed to a diverse and inclusive workplace.