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Machine Learning Engineer

Clay

San FranciscoFull-time$170k – $300kPosted Aug 14, 2026

Job description

ABOUT CLAY AI is unleashing the biggest wave of company creation in history. Clay's mission is to be the engine those companies use to grow to their full potential. Clay predicts the next best action for your business and then helps you take it. We started by aggregating the best data for B2B companies. Then, we built the infrastructure to run any personalized campaign on top of it, including emails, ads, landing pages, and workflows that make reps more productive.

Now, we're building agents that can help grow your company for you. We're already helping thousands of customers — including Anthropic, OpenAI, Google, and Visa — go to market with unique data, signals, and AI research. In 2026, we raised a $115M Series D https://www.linkedin.com/safety/go/?url=https%3A%2F%2Fwww.nytimes.

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WHAT YOU'LL DO

Build learning loops into the product Design and ship systems that allow Clay to learn and improve using user behavior and important business data. Build net-new recommendation-first experiences, from prototype through production. Build the ML and data platform Help stand up the infrastructure that underpins learning including data lake foundations and serving infrastructure.

Evaluate new tools for their ability to accelerate our product vision. Collaborate with our data science and data platform teams to ensure we’re all using a common data language. Make quality measurable Build eval systems and online monitoring so learning features are trustworthy and ensure they are actually positively impacting users’ experience of Clay.

Work across product teams The Learning Team maintains one shared roadmap serving all product teams; you'll partner with almost every product team at Clay to make their surfaces smarter.

WHAT YOU'LL BRING

5+ years in machine learning engineering or ML-heavy software engineering, with models and ML-powered features shipped to production Strong engineering fundamentals: you write production-quality code and own systems Experience with LLMs in production (prompting, evals, guardrails, fine-tuning) and/or classical ML (ranking, recommendations, propensity models) Experience building data-intensive systems: pipelines, feature infrastructure, retrieval, serving Pragmatic product sense — you optimize for the end user experience and business impact, and know when simple beats sophisticated Comfort with ambiguity — much of this platform is being built from the ground up A passion for the AI space: you stay up-to-date on the latest innovations and tools, and are excited to be at the frontier NICE TO HAVES Experience building recommendation systems, search ranking, or personalization Experience designing eval frameworks for LLM or ML systems Familiarity with modern data stack tools (Snowflake, dbt, Dagster) and data lake architectures Experience in fast-moving startup environments WHY CLAY This is a rare greenfield: the Learning Team is new, its charter comes straight from company leadership, and learning loops are central to Clay's product vision.

You'll define the architecture, set the standards, collaborate on the product vision, and ship the features that make Clay feel like it truly knows every customer. We value ownership, clear thinking, and work that has real impact.

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