Job summary
Job post source
This job is directly from Baylor Genetics
Job overview
The Sr. Bioinformatics ML/AI Engineer role at Baylor Genetics focuses on developing and deploying machine learning and AI applications for genomic and clinical data to enhance genetic testing workflows.
Responsibilities and impact
The engineer will design, develop, evaluate, and deploy ML/AI solutions, customize GenAI models, support data requirements, and collaborate with multidisciplinary teams in a clinical diagnostics environment.
Experience and skills
Candidates must have a Master’s or higher degree in a relevant field with 5 years of experience in genomic data analysis and application development, proficiency in clinical bioinformatics pipeline development, machine learning frameworks, cloud platforms like Azure, scripting languages, databases, and familiarity with advanced data visualization; DevOps experience is a plus.
Work environment and culture
Baylor Genetics promotes an inclusive and diverse workforce and operates in a regulated clinical diagnostics environment with collaboration among geneticists, bioinformaticians, software engineers, and IT professionals.
Company information
Baylor Genetics is a clinical genetic testing company committed to innovation in bioinformatics and genetic testing workflows.
Team overview
The candidate will join a multidisciplinary team including geneticists, bioinformaticians, software engineers, and IT infrastructure professionals.
Unique job features
The role involves working with cutting-edge ML/AI and GenAI technologies specifically tailored for genetic testing and clinical bioinformatics in a regulated environment.
Company overview
Baylor Genetics is a leading clinical diagnostic laboratory specializing in genetic testing and precision medicine. They generate revenue by offering a wide range of genetic testing services, including prenatal, pediatric, adult, and oncology diagnostics, to healthcare providers and researchers. Founded as a joint venture between Baylor College of Medicine and Miraca Holdings, the company leverages cutting-edge technology and expertise from one of the world's top medical schools. Their commitment to innovation and quality has established them as a trusted name in the field of genetic testing.
How to land this job
Position your resume to highlight expertise in genomic and clinical data modeling, emphasizing hands-on experience with machine learning frameworks like Huggingface and TensorFlow, as well as AI/GenAI application development relevant to clinical bioinformatics pipelines.
Focus on showcasing your skills in cloud computing, particularly with Azure, data engineering, and experience in next-generation sequencing data analysis, alongside scripting proficiency in Python and Bash.
Apply through multiple channels including Baylor Genetics' corporate careers page, LinkedIn, and specialized bioinformatics job boards to maximize your application visibility.
Connect with professionals in Baylor Genetics' bioinformatics or ML/AI divisions on LinkedIn; initiate conversations by referencing recent advancements in GenAI or asking about the integration of AI in clinical genetic testing workflows.
Optimize your resume for ATS by incorporating keywords from the job description such as 'bioinformatics ML/AI', 'clinical genetic testing', 'GenAI', 'variant interpretation', and 'cloud platform Azure' to ensure it passes automated screenings.
Leverage Jennie Johnson's Power Apply feature to automate tailored applications across multiple platforms and identify LinkedIn contacts for networking, enabling you to focus your time on interview preparation and skill enhancement.
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