Position: AI Engineer - LLM & Vector Database Optimization (Contractor)
Location: Onsite - South San Francisco
Duration: Contract through the end of 2025
Start: ASAP
About the Role:
We are seeking an experienced AI Engineer with a strong background in life sciences or healthcare to join our team in building a cutting-edge protocol authoring and review system. This system leverages large language models (LLMs) and a vector database for protocol creation, review, and data analysis. The ideal candidate will have hands-on experience with LLMs, a deep understanding of natural language processing (NLP), and technical expertise to optimize and enhance system performance.
This position requires someone with a blend of life sciences/healthcare expertise, NLP experience, and solid engineering skills who can directly contribute to system development and performance tuning.
Key Responsibilities:
- Benchmark and optimize the performance of our protocol authoring and review system, with a focus on NLP and vector search capabilities.
- Design and implement new features to enhance system effectiveness, user experience, and accuracy of protocol creation and review.
- Collaborate with the AI and engineering teams to integrate large language models (LLMs) into the system in a scalable and efficient manner.
- Improve vector database performance, ensuring fast, reliable query execution for protocol retrieval and comparison.
- Conduct stress testing and scalability assessments to ensure the system performs effectively under load.
- Develop new tools and methods for protocol data processing, including the use of embeddings and LLM-based features.
- Work closely with the scientists and other stakeholders to ensure the system meets industry-specific needs and regulatory standards.
Qualifications:
- 5+ years of direct experience applying AI in research and development
- Proven experience developing applications that integrate large language models (LLMs) such as GPT, Gemini, or similar.
- Strong background in natural language processing (NLP), particularly in text generation, summarization, and search optimization.
- Hands-on experience with vector databases.
- Proficiency in Python and experience with backend development.
- Experience with system benchmarking, performance testing, and feature optimization.
- Excellent problem-solving skills and the ability to work independently as well as part of a team.
Nice-to-Haves:
- Experience with cloud technologies, particularly in relation to hosting scalable AI models and vector databases.
- Experience with frontend development, particularly using Next.js or similar frameworks.
- Strong understanding of life sciences or healthcare industries and the specific challenges of protocol creation and review systems.
- Familiarity with the regulatory requirements of research protocols in life sciences and healthcare settings.