Machine Learning Engineer

About the role

Clay is building a self‑learning revenue engine where data, ML and AI are core to the product. As a Machine Learning Engineer you will join the Learning Team to create intelligence features that understand customers, power recommendations and enable new AI products.

Key responsibilities

• Design and ship learning loops that let Clay improve from user behavior and business data, delivering recommendation‑first experiences from prototype to production.
• Help stand up the ML and data platform, including data‑lake foundations, serving infrastructure, and evaluation of new tools that accelerate the product vision.
• Build evaluation systems and online monitoring to ensure learning features are trustworthy and positively impact user experience.
• Partner with product teams across the company to make every surface smarter, maintaining a shared roadmap.

Required profile

• 5+ years in machine‑learning engineering or ML‑heavy software engineering with production‑ready models and features.
• Strong engineering fundamentals; you write production‑quality code and own the systems you build.
• Experience with LLMs in production (prompting, evals, guardrails, fine‑tuning) and/or classical ML such as ranking, recommendations, and propensity models.
• Background building data‑intensive systems: pipelines, feature infrastructure, retrieval and serving.
• Pragmatic product sense, optimizing for end‑user experience and business impact.
• Comfort with ambiguity while building platform components from the ground up.
• Passion for AI, staying up‑to‑date with the latest innovations and tools.

Required skills

• LLMs in production (prompting, evaluation, guardrails, fine‑tuning)
• Classical ML techniques (ranking, recommendation, propensity modeling)
• Data pipelines and feature infrastructure
• Retrieval and serving systems
• Modern data‑stack tools: Snowflake, dbt, Dagster