ML Engineer: Build Learning Loops & AI Platform

AI Chopping Block; San Francisco, Northern (CA, KY); Hybrid; USD 150,000 - 230,000; Full time

Job summary

Clay is seeking a Machine Learning Engineer to join the Learning Team and build a self-learning revenue engine powered by data, ML, and AI. You’ll ship intelligence features that learn from customer data and behavior, ranking and recommendation experiences, and the ML platform enabling these capabilities.

You will design and implement systems for learning from user activity, stand up infrastructure for data lakes and serving, and collaborate across product teams to ensure a unified data language

Qualifications

• 5+ years in machine learning engineering or ML-heavy software engineering.
• Strong engineering fundamentals: 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 — optimize for end user experience and business impact.
• Comfort with ambiguity — platform built from the ground up.
• A passion for the AI space and staying up-to-date with innovations.

Responsibilities

• Build learning loops into the product and ship systems that learn from user data and business signals.
• Build the ML and data platform, including data lake foundations and serving infrastructure; evaluate new tools with product vision.
• Make quality measurable with eval systems and online monitoring to ensure positive user impact.
• Work across product teams with Learning Team roadmap to make surfaces smarter.

Skills

Machine learning

Production code

LLMs in production

Data pipelines

Product sense

Ambiguity tolerance

Tools

Snowflake

dbt

Dagster

Job description

Clay is seeking a Machine Learning Engineer to join the Learning Team and build a self-learning revenue engine powered by data, ML, and AI. You’ll ship intelligence features that learn from customer data and behavior, ranking and recommendation experiences, and the ML platform enabling these capabilities.

You will design and implement systems for learning from user activity, stand up infrastructure for data lakes and serving, and collaborate across product teams to ensure a unified data language