Careers at Omic
Join the team building biological superintelligence to end disease.
Why Join Omic?
Work on the Frontier
LLM-enabled agentic biology is brand new. You'll be building capabilities that didn't exist six months ago. Digital patients, autonomous discovery, reasoning agents—this is day one of a new paradigm.
Real Impact
We're not building features. We're discovering actual drugs for real diseases. Our pipeline has four programs in lead optimization. Your work will directly accelerate therapies that save lives.
Exceptional Team
Small, high-caliber team. Everyone here is building something they couldn't do anywhere else. Deep collaboration with pharma partners, academic labs, and the AI research community.
Open Positions
We're hiring across research, engineering, and operations. Remote-friendly with preference for Seattle.
Computational Biologist
Full-time•Remote/Seattle•$150K-$220K + equity
What You'll Do
- •Build AI agents that autonomously execute drug discovery workflows (target identification, validation, hit-to-lead optimization)
- •Work directly with LLMs to create tools for biological reasoning (literature synthesis, pathway analysis, experimental design)
- •Collaborate with pharma partners on real therapeutic programs in oncology, infectious disease, cardiovascular, and hematology
- •Design and implement digital patient models for predicting clinical outcomes before Phase I trials
What We're Looking For
- •PhD in computational biology, bioinformatics, systems biology, or related field
- •Strong Python programming skills and experience with machine learning/deep learning frameworks
- •Deep understanding of biological data (multi-omics, chemical structures, clinical data)
- •Passion for using AI to accelerate drug discovery and genuine interest in LLM-based approaches
- •Bonus: Experience with LLMs, agent frameworks, or drug discovery/medicinal chemistry
AI Research Engineer
Full-time•Remote/Seattle•$160K-$240K + equity
What You'll Do
- •Push the boundaries of LLM reasoning for biological and chemical domains (we're at 93.3% GPQA Diamond, but there's more to unlock)
- •Build agentic systems that can autonomously discover drugs—from target identification to lead optimization
- •Train and fine-tune models on biological data at scale (scientific literature, omics datasets, chemical structures, clinical trials)
- •Design novel architectures for biological superintelligence (multi-modal models, tool-using agents, reward models for scientific reasoning)
What We're Looking For
- •Strong ML/AI background—publications at top-tier conferences (NeurIPS, ICML, ICLR) or equivalent industry experience
- •Deep expertise in LLMs, transformer architectures, and modern training techniques (RLHF, instruction tuning, etc.)
- •Experience with agent frameworks, tool use, or multi-step reasoning systems
- •Interest in applying AI to biology/chemistry (no biology background required—we'll teach you)
- •Bonus: Experience with scientific/biological data, biotech/pharma domain knowledge, or building products with LLMs
Full Stack Engineer
Full-time•Remote/Seattle•$140K-$200K + equity
What You'll Do
- •Build the IDE for biology—beautiful, powerful interfaces where scientists and AI collaborate
- •Create interactive visualizations for complex biological data (molecular structures, pathway diagrams, patient cohorts)
- •Scale our platform to serve thousands of researchers across academia and pharma
- •Build integrations with internal pharma systems (ELNs, compound libraries, clinical databases) via MCP
What We're Looking For
- •Strong full-stack experience—TypeScript/React frontend + Node/Python backend
- •Product mindset—you care deeply about UX, performance, and building tools people love to use
- •Experience with real-time systems, data visualization, or complex web applications
- •Excited to build tools for scientific discovery (no biology background required)
- •Bonus: Experience with LLM-powered applications, data-heavy tools, or biotech/scientific software
Medicinal Chemist
Full-time•Seattle•$140K-$200K + equity
What You'll Do
- •Collaborate with AI systems to design and optimize small molecule therapeutics across our pipeline programs
- •Interpret computational predictions and translate them into actionable medicinal chemistry strategies
- •Design SAR studies and lead optimization campaigns guided by AI-predicted ADME, toxicity, and efficacy profiles
- •Work with CROs on synthesis and characterization of novel compounds for IND-enabling studies
What We're Looking For
- •PhD in medicinal chemistry, organic chemistry, or related field with 3+ years in drug discovery
- •Track record of lead optimization and advancing molecules toward clinical candidates
- •Strong understanding of ADME, PK/PD, and developability considerations
- •Comfortable working with computational tools and AI-driven design approaches
- •Bonus: Experience with structure-based design, fragment-based discovery, or one of our therapeutic areas
Machine Learning Engineer - Biology
Full-time•Remote/Seattle•$150K-$230K + equity
What You'll Do
- •Build ML infrastructure for biological data—ETL pipelines for multi-omics, protein structures, chemical libraries, clinical databases
- •Train and deploy models for molecular property prediction, target identification, and compound optimization at scale
- •Optimize inference and training infrastructure for large-scale biology models (AlphaFold, ESM, ChemBERTa derivatives)
- •Build evaluation frameworks to validate AI predictions against experimental results
What We're Looking For
- •Strong ML engineering fundamentals—distributed training, model deployment, data pipelines at scale
- •Experience with PyTorch/JAX and MLOps tools (Weights & Biases, Ray, Kubernetes, etc.)
- •Solid software engineering practices—version control, testing, CI/CD, production monitoring
- •Interest in biology/chemistry applications (we'll teach you the science)
- •Bonus: Experience with biological/chemical data, graph neural networks, or molecular modeling tools
Don't see your role?
We're always looking for exceptional people. If you're passionate about using AI to end disease, reach out—even if there's no open role that fits.