Staff Machine Learning Engineer, CustomerLake (ML/LLM)

Databricks • New York, NY

8d • $190,000 - $253,400

About The Position

Databricks is hiring a Staff Machine Learning Engineer to help build CustomerLake, its customer data platform, from the ground up. CustomerLake aims to bring enterprise-grade machine learning and AI personalization to organizations whose data is already on Databricks. The role is part of a small, nimble team in the NYC Engineering office and combines a 0-to-1 startup environment with Databricks’ resources.

The engineer will evaluate and improve machine learning and large language model approaches for personalization, examine model behavior in production, and build platforms and evaluation frameworks that help customers optimize for business outcomes such as purchases, retention, and product usage. The role also helps establish technical foundations and best practices as the work expands across products, while collaborating with product management, engineering, and design to turn ambiguous customer needs 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; practical ability to make models work well within a product.
• Experience with personalization based on customer behavior, ideally, 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 retrieval-augmented generation (RAG), prompt design, fine-tuning, and evaluation.
• Product mindset and ability to translate ambiguous customer problems into scrappy MVPs and iterate based on data and user feedback.
• High ownership and bias for action in 0-to-1 environments; comfort making 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 help develop novel methods and support innovation.

Responsibilities

• Evaluate machine learning and LLM approaches for CustomerLake personalization use cases, advance models and algorithms, and continuously improve quality.
• Inspect production model traces and behavior, understand model reasoning, and use those observations to tune and improve models.
• Build the platform and evaluation framework that enable customers to optimize for business outcomes such as purchases, retention, and product usage.
• Identify and pursue new directions and novel methods rather than only optimizing existing approaches.
• Partner with product management, engineering, and design to turn ambiguous customer problems into scalable, trustworthy solutions.
• Establish technical foundations and best practices for ML/AI personalization as the work grows across products.

Benefits

• The total compensation package may include eligibility for an annual performance bonus, equity, and benefits. Comprehensive benefits and perks are offered; regional details are available through the company.

What This Job Offers

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