Lead Bioinformatics AI Scientist
Baylor GeneticsTexas, United States
Posted November 4, 2025
Full Time
About the Company
Baylor Genetics is a leading diagnostic genomics partner headquartered in Houston’s Texas Medical Center, providing a comprehensive suite of clinically relevant genetic tests—including whole genome sequencing, whole exome sequencing, and targeted panels—to clinicians across all 50 states. Their services span family planning, pregnancy, neonatal and pediatric diagnostics, oncology, and rare disease evaluation, supported by rapid turnaround times and integrated genetic counseling. By combining state‑of‑the‑art sequencing technology with expert genetic counselors, Baylor Genetics helps clinicians shorten diagnostic odysseys, guide precision medical management, and ensure that no patient with a genetic disorder is overlooked. The company’s commitment to accessibility, multidisciplinary support, and a broad testing menu distinguishes it as a trusted partner for precision medicine in the United States.
Job Description
Baylor Genetics is seeking a Lead Bioinformatics AI Scientist to advance innovation in bioinformatics R&D and data science. The individual will serve as a scientific and technical leader, driving the design, development, and implementation of advanced AI methods, algorithms, and workflows to enhance Baylor Genetics' clinical testing and genomic data analysis capabilities.
Requirements
- Master's or higher degree in Bioinformatics, Machine Learning and AI, Computer Science, Data Science or related quantitative field
- 8+ years of professional experience in bioinformatics, AI application development, machine learning and/or genomic data analysis
- Hands-on experience in state-of-the-art GenAI application development, LLM model turning, agentic AI, and model context protocol (MCP)
- Hands-on experience in building and/or adopting novel AI and GenAI solutions for business specific applications
- Hands-on experience in automated and scalable AI/GenAI application evaluation, development, and deployment in the production environment
- Strong experience in cloud platform (Azure, AWS, GCP) and data services (data lakehouse/data warehouse)
- Experience in context-aware OCR
- Experience in databases, including SQL and no-SQL
- DevOps experience such as unit testing, CI/CD is a plus