Staff Machine Learning Engineer, CustomerLake (ML/LLM)

The shape of it

In the posting’s own words

As one of the first engineers in the NYC Engineering office, you'll join a small, nimble team building new products from the ground up. We're building CustomerLake, the Customer Data Platform on Databricks, to bring enterprise-grade ML and AI personalization to every company whose data already lives on Databricks. The best B2C and B2B brands have historically relied on in-house ML/AI teams to power personalization, recommendations, churn and lifetime-value modeling, and audience targeting. Our goal is to deliver that same capability to companies that don't have an in-house team but already have their data in order on Databricks. This is a true 0-to-1 environment, combining the excitement of a startup with the resources of a tech leader like Databricks.

What it asks for · 7

• 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

Also a plus

• Experience in martech, ideally a go-to-market or business use case with an analytical (rather than purely transactional) angle
• An academic or research background that can help us innovate and develop novel methods

What the job covers

• 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

Tools and skills named

Words the posting leans on

• data8×
• product8×
• customer7×
• models6×
• experience5×
• personalization5×
• building4×
• business4×
• already3×
• cases3×
• customerlake3×
• engineering3×
• evaluation3×
• improve3×
• llm3×
• ml/ai3×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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