Machine Learning Engineer

Responsibilities

• Design and ship learning loops that use user behavior and business data to improve Clay’s product.
• Build recommendation-first experiences from prototype through production.
• Develop the ML and data platform, including data lake foundations and serving infrastructure.
• Evaluate tools that can accelerate Clay’s product vision and collaborate with data science and data platform teams on shared data practices.
• Build evaluation systems and online monitoring to measure the quality and user impact of learning features.
• Partner with nearly every product team through the Learning Team’s shared roadmap.

Requirements

• 5+ years of experience in machine learning engineering or ML-heavy software engineering.
• Experience shipping models and ML-powered features to production.
• Strong software engineering fundamentals and experience owning production systems.
• Production experience with LLMs, including prompting, evaluations, guardrails, or fine-tuning, and/or classical ML such as ranking, recommendations, or propensity models.
• Experience building data-intensive systems, including pipelines, feature infrastructure, retrieval, or serving.
• Pragmatic product sense focused on user experience and business impact.
• Experience building recommendation systems, search ranking, or personalization is preferred.
• Experience designing evaluation frameworks for LLM or ML systems is preferred.
• Familiarity with Snowflake, dbt, Dagster, and data lake architectures is preferred.
• Experience in fast-moving startup environments is preferred.

Benefits

• Employees can work for free with world-class coaches specializing in creativity, management, and more.