Translational Genomics AI/ML Scientist

Location: Durham, NC, United States of America; hybrid work

Company

A global agricultural technology organization developing precision breeding, biotechnology, and digital platforms to improve crop performance, food security, and sustainable farming.

What you will do

• Design and deliver AI/ML-enabled genomics capabilities for trait discovery, genomic prediction, and breeding decisions.
• Develop, validate, and operationalize graph machine learning, foundation models, knowledge graphs, and explainable AI methods.
• Build scalable bioinformatics and machine-learning workflows integrating genomic variation, annotations, expression data, pathways, phenotypes, and literature evidence.
• Create biological data representations, feature-engineering strategies, and predictive models that capture complex genomic relationships.
• Collaborate with geneticists, breeders, molecular biologists, data scientists, software engineers, and product teams.
• Document methods, validate models, communicate results and limitations, and support reproducible handover to research and product teams.

Requirements

• PhD in Bioinformatics, Computational Biology, Genomics, Genetics, Computer Science, Machine Learning, Statistics, Applied Mathematics, or a related discipline.
• Strong background in genomics, quantitative genetics, population genetics, or computational biology.
• Expertise in machine learning and statistical modeling, with proficiency in Python and scientific computing.
• Experience working with large-scale biological datasets and a strong publication or research record.
• Excellent communication and collaborative problem-solving skills.
• Must be authorized to work in the United States without sponsorship.

Nice to have

• Experience with graph-based genomic representations, GNNs, GATs, graph embeddings, or network analytics.
• Experience with foundation models, transformers, DNA language models, or biological large language models.
• Knowledge of knowledge graphs, semantic technologies, biological ontologies, or AI-assisted scientific research workflows.
• Experience with AWS, Snowflake, distributed computing, MLOps, or production AI environments.
• Background in plant genomics, breeding, crop science, or agricultural biotechnology.

Culture & Benefits

• Collaborative culture focused on belonging, professional development, and work-life balance.
• Flexible work options.
• Medical, dental, and vision benefits starting on the first day.
• 401(k) plan with company match, profit sharing, and retirement savings contribution.
• Paid vacation, paid holidays, parental leave, education assistance, wellness programs, and corporate discounts.