1 day ago
Base Salary
$170k - $300k/yr
Responsibilities
- Design and ship learning systems that use customer data and behavior to improve Clay’s products.
- Build recommendation-first experiences and other AI-powered product features from prototype through production.
- Develop ML and data platform infrastructure, including data lake foundations and serving infrastructure.
- Build evaluation systems and online monitoring to measure the quality and user impact of learning features.
- Partner with data science, data platform, and product teams across Clay on a shared learning roadmap.
- Evaluate new tools and help define architecture and engineering standards for the Learning Team.
Requirements
- 5+ years of experience in machine learning engineering or ML-heavy software engineering.
- Production experience shipping models and ML-powered features.
- Strong software engineering fundamentals, including writing production-quality code and owning systems.
- Experience with LLMs in production, 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 judgment focused on user experience and business impact.
- Preferred experience with recommendation systems, search ranking, personalization, or evaluation frameworks for LLM or ML systems.
- Preferred familiarity with Snowflake, dbt, Dagster, and data lake architectures.
- Preferred experience working in fast-moving startup environments.
Benefits
- Employees can work with world-class coaches specializing in creativity, management, and more.
- The role offers a greenfield opportunity to define architecture, set standards, collaborate on product vision, and build the Learning Team’s charter.
Tech Stack
dbtSnowflake
Categories
About Clay Labs
Clay Labs builds a go-to-market data and automation platform that lets revenue teams discover prospects, enrich records from many providers, and personalize multichannel outreach. Delivered as a SaaS product with APIs and a data marketplace, it serves sales, marketing, and growth teams at startups and enterprises. The privately held company is headquartered in New York and is backed by investors including Sequoia Capital and CapitalG.