Machine Learning Engineer
San Francisco, CA - USA
Department:
Job Summary
Our mission is to help organizations turn any growth idea into reality.
We see growth as a creative practice not a formula. Finding and reaching your best-fit customers takes unique ideas and constant iteration. As AI makes execution faster and tactics easier to copy creativity is the only lasting advantage. Were already helping thousands of customers including Anthropic Notion Google and Ramp go to market with unique data signals and AI research.
In 2025 we raised a $100M Series C backed by world-class investors including Sequoia CapitalG and First Round and crossed $100M in revenue.
In 2026 we announced our second employee tender offer in 9 months at a new $5B valuation. We also launched a community equity round for our customers agency partners and club members.
Some things to know about us:
Our community includes 11000 customers 150 integration partners 125 agencies 50 Clay clubs and 30k members on Slack.
All employees can work for free with world-class coaches who specialize in creativity management and more.
Our operating principles including negative maintenance and non-attached action guide our work. Read more about them here.
Read about us in the NYT Forbes First Round Review and more.
Hear from our employees directly on our Glassdoor page!
Clays ambition is to build a self-learning revenue engine: a product that gets smarter every time someone uses it. This means data ML and AI are at the heart of everything we are building. Were looking for a Machine Learning Engineer to join the Learning Team: a centralized group of MLEs and data scientists whose charter is building the intelligence engine that powers learning loops across every surface of the product.
Youll ship intelligence features at the heart of the product: systems that learn a customers business from their data and behavior ranking and recommendation experiences net new 0 to 1 AI products and the ML platform that makes all of it possible.
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 were 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; youll partner with almost every product team at Clay to make their surfaces smarter.
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
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
This is a rare greenfield: the Learning Team is new its charter comes straight from company leadership and learning loops are central to Clays product vision. Youll 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.
Required Experience:
IC
About Company
Implement your creative growth ideas to build pipeline for your sales team. First, maximize your data coverage with 75+ enrichment tools and our AI agent. Then, use AI to craft the perfect outreach.