We are seeking a seasoned machine learning and AI application engineer with strong knowledge and hands-on experience in genomic/clinical data modeling and machine learning, AI/GenAI application development, data engineering, and cloud computing. This role requires expertise in various technologies and the ability to adapt to a fast-changing environment.
Qualifications:
- Education:
- Master's or higher degree in Computer Engineering, Data Science, Machine Learning, Data Modeling, or related field.
- Five (5) years of experience in genomic data analysis and application development.
- Experience:
- Hands-on experience in human genetics/multi-omics data modeling and application development, especially in next-generation sequencing data.
- Proficiency in machine learning frameworks (Huggingface, TensorFlow) and automated, scalable AI/GenAI application evaluation, development, and deployment.
- Experience with RAG AI framework and scripting languages like Bash and Python.
- Strong experience with cloud platforms (Azure) and data services (data lakehouse/data warehouse).
- Familiarity with databases (SQL and No-SQL) and advanced data visualization techniques.
- DevOps experience, including unit testing and CI/CD, is a plus.
- A strong curiosity and ability to learn quickly and adapt to a fast-changing environment.
Duties and Responsibilities:
- Act as the subject matter expert (SME) in ML/AI application development within a clinical genetic testing setting, providing hands-on support to build the company’s next-generation ML/AI platform.
- Design, develop, evaluate, and deploy state-of-the-art ML/AI solutions to extract insights from genetic, phenotypical, and clinical datasets.
- Evaluate and customize GenAI models based on internal and external datasets to enhance the overall performance of the genetic testing workflow.
- Utilize AI/ML and GenAI capabilities to support internal and external data requirements, responding to the growing demands of the business.
- Collaborate in a multidisciplinary and regulated clinical diagnostics environment with geneticists, bioinformaticians, software engineers, and IT infrastructure professionals.
Physical Demands and Work Environment:
- Frequently required to sit, stand, and utilize hand and finger dexterity.
- Frequently required to talk or hear, and utilize visual acuity for equipment operation, reading technical information, and keyboard use.
- Occasionally exposed to bloodborne and airborne pathogens or infectious materials.
EEO Statement:
Baylor Genetics is proud to be an equal opportunity employer dedicated to building an inclusive and diverse workforce. We do not discriminate based on race, religion, color, national origin, sex, sexual orientation, age, gender identity, veteran status, disability, genetic information, pregnancy, childbirth, or related medical conditions, or any other status protected under applicable federal, state, or local law.
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