3 months ago
San Mateo, CA, USAStaff+
Base Salary
$220k - $280k/yr
Responsibilities
- Own the architecture for a hybrid search engine that improves precision and recall.
- Design and scale personalization algorithms for product recommendations.
- Lead the fine-tuning of LLMs and encoders for construction domain tasks.
- Architect and optimize vector database strategies for efficient retrieval.
- Collaborate with product managers and designers to integrate AI components.
- Participate in the complete product lifecycle from design to deployment.
- Build scalable products that handle large data volumes efficiently.
- Design end-to-end data and ML pipelines for production integration.
- Lead research efforts to explore cutting-edge technologies.
- Maintain high standards in code quality and innovation.
Requirements
- Bachelor’s or Master’s degree in Science or Engineering; PhD preferred.
- Deep understanding and hands-on experience in Search, Ranking, and Recommendation systems.
- Expertise in Python and training deep learning models using PyTorch or TensorFlow.
- Ability to drive high standards for clean and efficient code.
- Experience with Learning to Rank, BM25, and hybrid retrieval strategies is preferred.
- Hands-on experience with Vector Databases and optimizing embedding spaces.
- Expertise in fine-tuning Large Language Models for semantic search.
- Experience building evaluation frameworks for search and managing embedding lifecycles.
- Familiarity with agentic frameworks for complex reasoning chains is a plus.
- Track record of publications in top-tier conferences or contributions to open-source projects is preferred.
Benefits
- Competitive salary and discretionary bonus, plus equity options.
- Unlimited PTO policy.
- Medical, dental, and vision coverage.
- Flexible hybrid work environment.
- Regular team offsites and a budget for professional development.