AI Researcher

You will work closely with our team of multi-disciplinary scientists to choose what models, metrics, and new features maximize our success. You will also work with our Product and Applications Lead to understand what partners need from our models. This role suits a machine learning researcher who has applied models to drug discovery, ideally in a preclinical program, and wants to shape the modeling direction at a small company. We will set the level (AI Researcher or Senior AI Researcher) based on experience., * Improve Ptarmigan: Develop new architectures, training objectives, and data representations that improve how well Ptarmigan predicts compound-protein engagement.

• Build new models: Develop protein-ligand interaction and generative chemistry models that support hit discovery, hit-to-lead campaigns, and lead optimization, particularly for targets that lack structures or known binding pockets.
• Evaluate rigorously: Design benchmarks, held-out splits, and baselines (e.g., docking and structure-based co-folding models) that reflect how the models will be used in practice, and report where they fail.
• Close the loop with the lab: Work with our experimental scientists to pick compounds and experiments for prospective validation and active learning, so that each round of data improves the next model.
• Build agentic tools: Build tools and agents that call our models through APIs and MCP, so that scientists and AI agents can run virtual screens and interpret the results.
• Ship your work: Write tested, version-controlled code and take models from research to production, working with our team on training and inference infrastructure in the cloud.
• Share results: Present plans and results at R&D meetings and to partners, and publish papers, preprints, and open-source software where it advances our science.

Research Skills, Artificial Intelligence (AI), Cancer, Biotech and Pharmaceutical, Medical Products, Proteomics, Disease, Artificial Intelligence (AI), Research Skills, Small Molecules, Talus Bio is looking for an AI Researcher to join the team full-time in our Seattle office (this is an in-person role). This person will be naturally curious, results-driven, and eager to work in a small preclinical biotech environment., Required

• Ph.D. in machine learning, computer science, computational chemistry, bioinformatics, or a related field with 2+ years of industry or postdoctoral experience, or an M.S. with 5+ years of industry experience
• Experience applying machine learning to small molecules or protein-ligand interactions in a drug discovery setting
• Experience designing and training deep learning models on molecular or protein data with PyTorch or a similar framework
• Fluency in Python and Git, and experience training models on GPUs in the cloud
• Ability to explain models, their results, and their limitations to chemists, biologists, and other non-computational colleagues
• Experience building software and managing projects using agentic AI tools, such as Claude Code or OpenAI Codex.
• Able to work onsite in Seattle

Preferred

• Experience building models that were used in a preclinical program for hit discovery, hit-to-lead, or lead optimization
• Experience with generative models for small molecules (e.g., diffusion, flow matching, or chemical language models)
• Experience with building protein language models or structure-based models (e.g., Boltz, AlphaFold, or docking)
• Experience with proteomics, mass spectrometry, or chemoproteomics data, including activity-based protein profiling
• Experience building custom LLM agents or tools that use the Model Context Protocol (MCP)
• A record of publications or open-source software in machine learning for biology or chemistry
• Experience with active learning, uncertainty estimation, or Bayesian optimization
• Experience leading ML projects or mentoring other scientists

This position is only open to applicants that are legally authorized to work in the US.

The salary range for this position is $140,000-210,000 per year.

Despite being a small early-stage biotech, Talus Bio’s first priority is the wellbeing of all our employees and their families, both inside and outside of the lab. As part of this commitment, we have put a great deal of care into developing a cost-effective and comprehensive benefits package for our team.

Our benefits package includes but is not limited to the following:

• Medical/dental/vision insurance coverage with 100% company-paid premiums for employees and 60% company-paid for dependents
• Commuter and transportation reimbursement program
• 401(k) plan with a Talus Bio contribution (regardless of employee contribution)
• Basic Life and AD&D insurance coverage with 100% company-paid premiums
• Short- and Long-Term Disability insurance coverage with 100% company-paid premiums
• Paid sick leave
• Generous paid time off and holidays, including a paid end-of-year shutdown
• Weekly meals, snacks, and drinks
• Flexible working hours

Talus Bioscience, a venture-backed early-stage biotechnology company, is at the forefront of developing innovative AI models, and using those models to deliver much-needed medicines. Driven by the belief that “nothing is undruggable,” we harness cutting-edge proteomics and frontier AI during the initial stages of discovery to unlock previously inaccessible targets in cancer, autoimmunity, and other high burden diseases., Talus Bio is committed to creating a high-performing, inclusive, and supportive workplace. We believe that having employees, interns, and contractors with diverse backgrounds enables Talus Bio to best achieve our mission to bring new therapeutics to patient communities around the world. We recognize that opportunities in the life sciences have historically excluded and continue to disproportionately exclude certain groups, and we strongly encourage all qualified people to apply.