Responsibilities
- Continuously improve search quality using models, data, tools, or other scalable methods
- Design and implement foundational elements of the search platform and machine learning stack
- Develop and assess retrieval, ranking, and classification models, including large language models
- Deploy machine learning models, ranging from traditional boosting methods to LLMs, with scalability and performance in mind
- Construct and refine RAG systems for accurate grounding and answer synthesis
- Work closely with Data, AI, Infrastructure, and Product teams to enable rapid, high-quality delivery
Compensation
Competitive salary and equity package
Work Arrangement
Hybrid or remote options available
Team
Collaborative environment focused on AI-driven search innovation
Requirements
- Strong background in machine learning with hands-on experience in search or information retrieval
- Proficiency in Python and experience with deep learning frameworks
- Experience training and deploying scalable ML models in production environments
- Familiarity with LLMs, RAG architectures, and model evaluation techniques
- Ability to work across teams and drive technical projects independently
Available for qualified candidates