AI Omics Scientist III

AI Omics Scientist III – Remote PST

The AI Omics Scientist III is a senior‑level contributor responsible for leading the development of scalable AI/ML solutions in support of complex genomic and multi‑omics research. This role integrates deep learning, advanced statistical modeling, and biomedical interpretation to accelerate insights in diagnostics, therapeutic development, and clinical decision‑making.

$130,000 - $170,000 per year. You are eligible for a Short‑Term Incentive Plan with the target at 10% of your annual earnings; terms and conditions apply.

• Lead the design and development of machine learning models for omics analysis and clinical AI tools
• Drive integration of AI with multi‑omics datasets, including genomics, transcriptomics, proteomics, and clinical phenotypes
• Apply deep learning architectures (CNNs, RNNs, transformers, LLMs) for predictive and generative analysis
• Contribute to production‑ready deployment of models using MLOps and cloud‑native tools
• Mentor junior scientists, guide project direction, and ensure scientific rigor in AI‑driven research
• Publish high‑impact findings and collaborate with external partners on AI method development
• Ensure reproducibility and interpretability of models in a regulatory and clinical context (e.g., CAP, CLIA)
• Collaborate with software engineering teams to scale tools to production and integrate with user‑facing platforms
• This position may serve as a technical lead or project owner. While it does not have direct reports, it includes mentoring of junior scientists and cross‑functional project coordination
• Other duties as assigned

• PhD in Computational Biology, Bioinformatics, AI/ML, or a related field with 4+ years of post‑degree experience, or MS with 6+ years of relevant experience
• Strong grounding in omics technologies (e.g., RNA‑seq, WGS, single‑cell, proteomics) and biomedical informatics
• Deep understanding of machine learning theory, statistical modeling, and biological interpretation
• Expert in Python and advanced ML frameworks (e.g., PyTorch, Tensor Flow, JAX, Hugging Face)
• Proficiency with GPU‑based model training, performance tuning, and distributed learning frameworks
• Experience in MLOps tools (MLflow, DVC), containerization (Docker, Kubernetes), and cloud platforms (AWS/GCP)
• Deep knowledge of omics‑specific processing pipelines and tools (e.g., GATK, Nextflow, Snakemake)
• Experience with foundational models (e.g., BERT, BioBERT, GPT, Alpha Fold, or domain‑adapted LLMs)
• Familiarity with HIPAA‑compliant and regulated environments
• Strong communication skills for both technical and cross‑disciplinary collaboration
• 5+ years applying AI/ML in bioinformatics, biomedical, or healthcare domains
• Experience leading AI research initiatives or clinical deployment efforts
• Track record of peer‑reviewed publications, conference presentations, or open‑source contributions

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