Genomenon is an AI-driven biomedical intelligence company on a mission to save and improve lives by making biomedical information actionable. Rare diseases and cancer affect more than 30 million people in the U.S. alone and hundreds of millions globally, yet most patients still face long diagnostic journeys and limited treatment options. Our goal is clear and ambitious: to deliver the information that shapes diagnosis and treatment for every rare disease and cancer patient.
We sit at the intersection of AI, genomics, and real-world evidence. Genomenon transforms the global scientific literature into a literature-derived real-world evidence (RWE) engine for precision medicine—combining large-scale AI with expert human curation to deliver clean, clinically actionable datasets. This approach fills critical gaps left by EHR and claims data, especially in rare disease and oncology, by showing how patients actually present, progress, and respond to therapy.
We turn vast, complex biomedical data—spanning genomics, clinical evidence, and scientific literature—into trusted intelligence that helps clinicians make better diagnostic and therapeutic decisions, and supports life sciences organizations in bringing better therapies to market faster.
Our work has real, measurable impact. Genomenon’s platforms and services are used by more than 250 clinical laboratories and pharma organizations worldwide to support diagnostic interpretation, variant curation, and evidence-based decision-making across the drug development lifecycle.
Each year, our technology helps inform care for tens of thousands of patients facing rare, complex, and time-sensitive conditions—reducing uncertainty and delivering answers when they matter most.
What makes Genomenon unique is our ability to support both clinical diagnostics and pharmaceutical innovation on a shared foundation of advanced AI, deep domain expertise, and rigorously curated data.
- In the clinic, our solutions directly influence real-world patient outcomes.
- In pharma, we enable teams to harness literature-derived RWE across clinical trial development, regulatory, and commercial workflows—turning fragmented biomedical knowledge into a strategic asset and emerging as the trusted data layer for genomic diagnostics and precision therapeutics.
If you’re motivated by impact, energized by complexity, and excited to help shape the future of rare disease diagnosis and treatment, there’s no better place to do that work.
Genomenon /ge.gno.mai.non/Source language: ancient Greek
- Verb
to come into being
to be born out of need - Noun
the leader in genomic intelligence
Genomenon team members are thoughtful, ambitious, and mission-driven professionals working across states and countries. Our team brings together scientists, clinicians, engineers, and commercial leaders who collaborate as equals and learn from one another every day.
We value curiosity, accountability, and people who thrive in fast-moving, high-impact environments.
We are guided by our core values:
- Always Learning: Approach challenges with curiosity and a growth mindset
- Data-Driven: Ask a lot of questions and look to the evidence for answers
- Humbly Confident: Aware of the value that we and others bring to the team
- Customer & Patient Driven: Put patients and customers first in everything we do
- True Grit: Embody passion and persistence, and aren’t afraid of hard work
We are seeking an AI Scientist Engineer to design, develop, and deploy advanced AI systems that integrate multimodal deep learning, graph machine learning, and causal inference. This role bridges cutting-edge research with production-grade engineering - ideal for someone who thrives at the frontier of model innovation and scalable system design.
Responsibilities
• Develop multimodal AI models integrating text, graph, and structured data
• Prototype and productionize graph neural networks (e.g., HGT, GraphSAGE, transformer-based GNNs)
• Build, train, and evaluate large-scale transformer models for scientific and biomedical NLP
• Design and implement causal inference components, including ATE and CATE estimation
• Collaborate closely with domain experts and product teams to translate research into deployed capabilities
• Ensure model safety, calibration, provenance, and regulatory compliance
• Contribute to production ML workflows, including model training, evaluation, and deployment pipelines
• PhD or Master’s degree in Computer Science, Machine Learning, Bioinformatics, or a related field
• 4+ years of hands-on experience in deep learning and machine learning research (or equivalent industry experience)
• Demonstrated expertise in one or more of the following: transformer architectures, graph machine learning, or causal modeling
• Strong proficiency in Python and modern ML frameworks (PyTorch and/or JAX)
• Experience designing and building developer-friendly command-line interfaces (CLIs), with fluency in Linux-based workflows and tooling
• Experience training models at scale, including distributed training and working with large-scale datasets
• Biomedical NLP or computational biology experience
• Experience building knowledge graphs or ontologies
• Experience with interpretability and hallucination suppression
Building a great company starts with building a diverse and inclusive team. We believe that people with different backgrounds, perspectives, and life experiences help us solve harder problems and build better solutions.
Genomenon is committed to inclusion across race, gender, age, religion, identity, disability, and background — in how we hire, how we work, and how we lead.
If you’re excited about the role but unsure whether you meet every qualification, we encourage you to apply. We’d rather review one more resume than miss the chance to meet someone exceptional.
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