Sr. Bioinformatics ML/AI Engineer

Baylor Genetics • Houston, TX

61d

About The Position

A seasoned machine learning and AI application engineer with strong knowledge and hands-on experience in bioinformatics, genomic/clinical data modeling, AI/GenAI application development, data engineering, and cloud computing.

Requirements

• Master's or higher degree in Computer Engineering, Data Science, Bioinformatics, Machine Learning, and Data modeling, or related field with five (5) years of experience in genomic data analysis and application development.
• Hands-on experience in clinical bioinformatics pipeline development, including secondary/tertiary analysis, variant interpretation and classification pipeline R&D, and automated report generation
• 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 (such as Huggingface, TensorFlow)
• Hands-on experience in automated and scalable AI/GenAI application evaluation, development, and deployment.
• Hands-on experience in RAG AI framework
• Hands-on experience with scripting languages, such as Bash and Python
• Strong experience in cloud platform (Azure) and data services (data lakehouse/data warehouse)
• Experience in context-aware OCR
• Experience in databases, including SQL and NoSQL
• Familiarity with advanced data visualization techniques

Nice To Haves

• 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

Responsibilities

• Serves as the SME in Bioinformatics ML/AI application development in a clinical genetic testing setting. Provides hands-on support towards building the company's next-generation bioinformatics ML/AI platform
• Designs, develops, evaluates, and deploys state-of-the-art ML/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 enhance the overall performance of the genetic testing workflow
• Supports both internal and external data requirements by leveraging AI/ML 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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Industry: Ambulatory Health Care Services
• Number of Employees: 251-500 employees