Lead Bioinformatics AI Scientist

Baylor Genetics

Lead Bioinformatics AI Scientist at Baylor Genetics focusing on AI-powered genomics research and data analysis. Develop innovative AI applications and enhance clinical testing capabilities with genomic insights.

Posted 5/16/2026full-timeRemote • 🇺🇸 United StatesSeniorWebsite

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformPythonPyTorchSQLTensorflow

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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

Comp & perks

Health insurance
Professional development opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

bioinformaticsAI application developmentmachine learninggenomic data analysisGenAI application developmentLLM model tuningagentic AImodel context protocol (MCP)human geneticsmulti-omics data modeling

Soft Skills

leadershipcollaborationadaptabilitycuriosity

Certifications

Master's degreePhD