Machine Learning Engineer
$170,000–$300,000 year
RemoteUnited States or San Francisco, California, United States
Job Summary
Design and ship systems that allow Clay to learn and improve using user behavior and business data, building net-new recommendation-first experiences from prototype through production. Build the ML and data platform by standing up infrastructure for data lake foundations and serving, while collaborating with data science teams to establish a common data language. Construct eval systems and online monitoring to ensure learning features are trustworthy and positively impact the user experience. Partner with nearly every product team to maintain a shared roadmap and make product surfaces smarter. Define architecture and set standards for this new, greenfield Learning Team as you ship features that make Clay feel like it truly knows every customer.
Required Qualifications
- 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
Desired Qualifications
- 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
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