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AI Researcher

Talus Bio

Seattle, WAFull-time$140–210K/yrPosted 2 days agoStill listed 2 days ago

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At a glance

Compensation
$140–210K/yr
Location
Seattle, WA
Schedule
Full-time
Work Authorization
Not specified

Olive focuses on jobs in the United States, including remote roles you can work from there.

Job overview

Talus Bio seeks an AI Researcher to improve its Ptarmigan model and develop models for drug discovery programs and partners. The role works with multidisciplinary scientists and product colleagues to guide modeling priorities, validate predictions experimentally, and translate research into production tools. The level will be set as AI Researcher or Senior AI Researcher based on experience.

Skills & qualifications

RequiredNice to have

Skills

Machine Learning for Drug Discovery, requiredDeep Learning, requiredMolecular Data Modeling, requiredProtein Data Modeling, requiredPyTorch, requiredPython, requiredGit, requiredCloud GPU Training, requiredModel Communication, requiredAgentic AI Tools, requiredPreclinical Drug Discovery Modeling, nice to haveGenerative Chemistry, nice to haveProtein Language Modeling, nice to haveStructure-Based Modeling, nice to haveProteomics, nice to haveMass Spectrometry, nice to haveChemoproteomics, nice to haveActivity-Based Protein Profiling, nice to haveLLM Agent Development, nice to haveModel Context Protocol, nice to haveActive Learning, nice to haveUncertainty Estimation, nice to haveBayesian Optimization, nice to haveML Project Leadership, nice to haveMentoring, nice to have

Qualifications

PhD in Related Field or MS, required2+ Years Industry or Postdoctoral Experience or MS+5 Years Industry Experience, requiredSmall Molecule or Protein-Ligand ML Experience, requiredModel Training Experience, requiredSoftware and Project Management Experience, requiredUS Work Authorization, required

Benefits

Medical Insurance
Dental Insurance
Vision Insurance
401(k) Match
Paid Time Off

Full job description

About Talus Bio

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.

AI Researcher Job Description

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.

You will improve Ptarmigan, our structure-free model that predicts which small molecules engage which proteins across the human proteome, and you will build new models for our drug discovery programs and partners. Ptarmigan learns from Talus Bio's own chemoproteomics data: hundreds of millions of compound-protein measurements collected in native human cells, including on transcription factors and other proteins without good structures. We measure success by delivering value beyond in silico metrics: successful models drive early discovery and accelerate the optimization of molecules moving toward the clinic.

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.

What you will do

  • 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.

Qualifications

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.

Salary and Benefits

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

Our Commitment to Diversity & Inclusion

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.

Talus Bioscience, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

How this job compares

Set against the 581 open Machine Learning Researcher jobs on Olive Jobs, counted November 13, 2026.

Pay
  • This posting$140–210K/yr
  • Washington median$163–229K/yr32 salary ranges
  • US median$168–252K/yr345 salary ranges

This range's midpoint, $175K, is 11% below the Washington median midpoint ($197K) — in the middle half of Machine Learning Researcher salary ranges in Washington.

Openings
Olive Jobs lists 83 open Machine Learning Researcher jobs in Washington and 581 across the US. 6% of them nationwide are listed as remote or flexible.
Hiring the most in Washington
Experience
This posting asks for at least 2 years of experience; Machine Learning Researcher postings that state a minimum ask for 3 years at the median (220 postings).
Education
237 of the 581 open Machine Learning Researcher jobs (41%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on November 13, 2026. Figures based on too few postings are left out.

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