Staff Machine Learning Engineer, CustomerLake (ML/LLM)

Databricks • New York City, NY

7d

About The Position

Databricks is building CustomerLake, a Customer Data Platform on Databricks that brings enterprise-grade machine learning and AI personalization to companies whose data already lives on the platform. The goal is to make capabilities such as personalization, recommendations, churn and lifetime-value modeling, and audience targeting available to companies without in-house ML/AI teams. This is a 0-to-1 product-building environment in the New York City Engineering office, combining startup-style work with Databricks’ resources.

The Staff Machine Learning Engineer will advance ML and LLM approaches for CustomerLake personalization use cases, build systems for evaluating models against real business outcomes, and establish technical foundations and best practices for the growing ML/AI personalization effort. The role works closely with product management, engineering, and design to turn ambiguous customer problems into scalable, trustworthy solutions.

Requirements

• 10+ years of engineering experience, with a strong foundation across the full lifecycle 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.
• Experience with personalization based on customer behavior or transactions, such as recommendations, targeting, churn, or lifetime-value modeling.
• Proficiency in Python and modern ML frameworks such as PyTorch.
• Hands-on experience with model evaluation and monitoring AI quality in production.
• Familiarity with LLMs and generative AI, including RAG, prompt design, fine-tuning, and evaluation.
• Product mindset and ability to translate ambiguous customer problems into scrappy MVPs, then iterate based on data and user feedback.
• High ownership and bias for action in 0-to-1 environments, including pragmatic trade-offs, working with incomplete information, and driving projects from idea through launch and adoption.

Nice To Haves

• Experience in martech, ideally in a go-to-market or business use case with an analytical rather than purely transactional angle.
• Academic or research background that can support innovation and development of novel methods.

Responsibilities

• Evaluate ML and LLM approaches for CustomerLake personalization use cases, advance models and algorithms, and continuously improve quality.
• Inspect model behavior in production, including individual traces and reasoning, and use findings to tune and improve models.
• Build the platform and evaluation framework that help customers optimize for business outcomes such as purchases, retention, and product usage rather than vanity metrics.
• Identify and pursue new directions and novel methods for the team.
• Partner with product management, engineering, and design to turn ambiguous customer problems into scalable, trustworthy solutions.
• Set the technical foundation and best practices for ML/AI personalization work as the effort grows across products.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed