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Dayhoff Labs

AI-driven molecular design and simulation

Research Engineer

AI ResearchConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • Demonstrated ability to use large language models to write software and build complex systems.
  • Hands-on experience with open-source models, including self-hosting, evaluation, and writing harnesses or scaffolding around them.
  • Strong Python skills and the ability to own complex technical systems end to end.
  • Comfort working across an unfamiliar codebase and shipping in areas outside prior expertise.
  • Sound engineering fundamentals, including version control workflows, testing, and reproducible environments.

Responsibilities

  • Use large language models and coding agents to build software and complex systems, and advance internal agentic systems used to write code and maintain infrastructure.
  • Self-host and evaluate open-source models, and write harnesses, tooling, and scaffolding that make agents reliable for workflows.
  • Apply agents to scientific questions through research, experimentation, and analysis, in addition to software development.
  • Contribute across maintenance and research projects as priorities shift, including internal tooling, data, and model work.
  • Maintain cloud infrastructure and development environments.

Desired Qualifications

  • Background in biology, chemistry, or a related scientific domain.
  • Scientific computing or machine learning/research-tooling experience.
  • Substantial professional software engineering experience.
  • Experience building or operating agentic systems, including multi-step tool use, orchestration, and evaluation harnesses.
  • Familiarity with cloud infrastructure such as AWS or GCP, containerization, and infrastructure as code.

About the Company

Dayhoff Labs

AI-driven molecular design and simulation

Dayhoff Labs develops AI models and computational platforms to solve complex problems in chemistry, biochemistry, and synthetic biology. Its tools help researchers design, optimize, and simulate molecules such as enzymes and catalysts, enabling faster discovery and more sustainable chemical processes. By combining machine learning, computational chemistry, and laboratory work, it offers machine-assisted workflows that integrate experimental data and collaboration with researchers, with a strong emphasis on open science. The company aims to shorten discovery timelines, reduce costs and environmental impact, and broaden access to AI-powered molecular design for academia and industry.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
Boston, MA
Founded
2022

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