Note: The job is a remote job and is open to candidates in USA. Baylor Genetics is seeking an accomplished and visionary Lead Bioinformatics AI Scientist to advance innovation within the Bioinformatics R&D and Data Science organization. This individual will serve as a scientific and technical leader, driving the design, development, and implementation of advanced AI methods, algorithms, and workflows for clinical testing and genomic data analysis.
Responsibilities
- 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
Skills
- 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
- Strong curiosity and the ability to learn quickly and adapt to a fast-changing environment
- Strong scientific reasoning and analytical problem-solving skills
- Proven ability to lead R&D initiatives from concept through validation and deployment
- Deep understanding of genomic data, AI applications, and biological context
- Excellent written and verbal communication for technical and clinical translation
- Collaborative mindset and ability to work across disciplines
- Commitment to innovation, quality, and patient-centered outcomes
- DevOps experience such as unit testing, CI/CD is a plus
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