Chai Discovery Logo

Chai Discovery

Research Scientist, Applied Research

Posted 7 Days Ago
Be an Early Applicant
In-Office
San Francisco, CA, USA
Entry level
In-Office
San Francisco, CA, USA
Entry level
Develops methods to improve foundation models for drug discovery through targeted data generation, model evaluations, and post-training recipes. The role collaborates with pre-training researchers, research engineers, and biological scientists to address protein, antibody, and small-molecule modeling problems. Candidates should bring strong quantitative and machine learning expertise, software engineering depth, and familiarity with biological modeling methods such as AlphaFold, RFDiffusion, ProteinMPNN, and ESM.
The summary above was generated by AI
About Chai Discovery

Chai Discovery builds the computer-aided design suite for molecules. Eli Lilly, GSK, Pfizer, Bristol Myers Squibb, argenx and Novartis all use Chai to power drug discovery programs. AI is reinventing life sciences the same way it reinvented software engineering, and our team is building that future.

We train frontier models that learn the underlying foundations of biochemical structure and interaction. We pair this with a computational workspace to iterate on molecules from idea to medicine, helping scientists move faster and develop medicines beyond the reach of existing methods.

We value diverse perspectives and are ready to find greatness in unexpected places.

About the role

We are hiring research scientists to improve the real-world performance of our foundation models. The work involves planning targeted data generation campaigns, designing evals that accurately measure model performance, and formulating post-training recipes aimed at making models useful for real drug discovery problems.

We prioritize simple, robust methods over intricate solutions built for narrow problems. We particularly value researchers who can formalize messy biological problems using methods from other fields.

You will work in tight loops with our pre-training researchers, research engineers and science team. Your work will ship fast and you'll see your results reach real therapeutic programs across industry.

About you

We look for technical depth paired with interest in the underlying biology. Biological background is not required. All of the following are positive signals:

  • Published research in machine learning for protein, antibody, or small-molecule modelling.

  • Fluency in the technical details of protein language, structure prediction, and design models (AlphaFold, RFDiffusion, ProteinMPNN, ESM, etc).

  • Strong quantitative background (CS, math, or physics), particularly in probability, statistics, and machine learning.

  • Deep software engineering expertise, with experience working in large codebases.

We are happy to bet on rising talent.

We offer

The opportunity to work at the vanguard of AI research and frontier biology, with world-class people, on a mission that matters. We protect and promote a culture of high velocity and ownership. We compensate our team accordingly.

HQ

Chai Discovery San Francisco, California, USA Office

San Francisco, California, United States

Similar Jobs

Yesterday
Hybrid
Santa Clara, CA, USA
192K-305K Annually
Senior level
192K-305K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
Conduct advanced research in quantum error correction and fault-tolerant quantum computing. Develop novel error-correction codes, logical operations, synthesis methods, and fault-tolerance techniques. Collaborate with Product, Engineering, Applied Research teams, external partners, and quantum hardware teams to integrate quantum software and hardware components. Drive technical innovations from theory toward practical quantum computing products.
Top Skills: Applied Machine LearningCudaDeep LearningFault-Tolerant Quantum ComputingHigh-Performance ComputingNvidia GpusQuantum ComputingQuantum Error CorrectionScientific Computing
Yesterday
In-Office
San Francisco, CA, USA
210K-230K Annually
Senior level
210K-230K Annually
Senior level
Hardware
Develop agentic AI capabilities across Lumafield’s stack, including benchmarking LLMs, VLMs, and perception encoders; fine-tuning and post-training models; building deployed agents and evaluation harnesses; and creating evaluations that predict real-world performance. The role partners with product and engineering teams to improve agentic workflows and applies machine learning to specialized manufacturing, design, spatial, and perception data.
Top Skills: Ai AgentsLlmsPythonVision TransformersVlms
2 Days Ago
In-Office
San Francisco, CA, USA
210K-230K Annually
Senior level
210K-230K Annually
Senior level
Hardware
Lead the development of manufacturing automation methods for processes including die casting, injection molding, and CNC machining. Design and iterate experiments, integrate robots, manufacturing equipment, and CT scanners, and develop autonomous manufacturing processes. Work with customers to define pilot programs and travel internationally to manufacturing sites. The role requires applied machine learning, optimization, scientific computing, simulation, prototyping, and strong experimental judgment.
Top Skills: Analytical GeometryBrepCad KernelsCnc MachiningDie CastingIndustrial Ct ScanningInjection MoldingMachine LearningOptimizationPlc ProgrammingRoboticsScientific ComputingSimulation

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account