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Software Engineer - Scientific Models at Benchling | San Francisco

BenchlingSan Francisco, CA
On-site Full-time

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Experience Level

Mid to Senior

Qualifications

We are looking for candidates with:3+ years of experience in software engineering, with a strong foundation in building scalable platforms. Proficiency in programming languages such as Python, Java, or similar. Experience with machine learning frameworks and scientific computing. A passion for AI and its applications in biotechnology. Excellent problem-solving skills and a collaborative mindset.

About the job

Benchling creates software tools for scientists and biotech companies, supporting research and development across the globe. The platform serves more than 200,000 scientists, including teams at organizations like Sanofi and Moderna, as well as academic research labs. By connecting experiments, structured data, and AI-powered insights, Benchling works to reduce the time it takes for discoveries to reach real-world applications.

Role overview

This Software Engineer position focuses on integrating advanced scientific AI models into the Benchling platform. The main responsibility is to build a scalable system for hosting and managing scientific models, while also developing frameworks that allow model creators to bring their solutions into the Benchling environment.

What you will do

  • Develop and maintain a platform that supports scientific AI models at scale.
  • Create frameworks that make it easier for model developers to contribute to Benchling.
  • Experiment with new technologies to improve model integration and performance.
  • Work closely with internal teams and external partners to deliver solutions.
  • Help shape how scientists design molecules and apply AI in their research workflows.

Location

This role is based in San Francisco, CA.

About Benchling

Benchling is revolutionizing the biotech industry by harnessing the power of AI to enhance research and development processes. Our platform supports scientists in designing experiments and managing data, fostering innovation across top biopharma organizations and academic institutions.

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