Baylor Genetics pioneered the history of genetic testing. Now, we’re leading the way in precision diagnostics.
Lead Bioinformatics AI Scientist
Location
United States
Posted
15 days ago
Salary
0
Seniority
Senior
Job Description
Lead Bioinformatics AI Scientist
Baylor Genetics
• Serves as the visionary leader in Bioinformatics AI application development in a clinical genetic testing setting. • Provides technical guidance and hands-on support towards building company’s next-generation bioinformatics AI platform. • Identifies, prototypes, and develops state-of-the-art AI applications to revolutionize clinical testing and genomic analysis workflow. • Designs, develops, evaluates, and deploys novel AI solutions to gain valuable data insights based on the genetical, phenotypical, and clinical datasets. • Evaluates, adopts, and customizes GenAI models based on both internal and external datasets to build next-generation clinical genetic testing platforms. • Supports both internal and external data requirements by leveraging AI and GenAI capabilities to keep up with the increasing demands of the business. • Collaborates in a multidisciplinary and regulated clinical diagnostics environment with geneticists, bioinformaticians, software engineers, and IT infrastructure professionals.
Job Requirements
- Master's or higher degree (PhD preferred) 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, including 3–5 years in a principal or leadership role.
- 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, especially in the field of clinical testing and genomic data analysis.
- Hands-on experience in automated and scalable AI/GenAI application evaluation, development, and deployment in the production environment requiring fast turn-around-time (TAT) and high reliability.
- Hands-on experience in human genetics/multi-omics data modeling and application development especially in next-generation sequencing data.
- Hands-on experience in machine learning framework (Huggingface, TensorFlow, PyTorch, etc.).
- Hands-on experience with scripting language, such as Bash and Python.
- 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.
- Strong curiosity and the ability to learn quickly and adapt to a fast-changing environment.
Benefits
- Health insurance
- Professional development opportunities
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