
Tamarind Bio provides scientists a no-code platform to design and optimize proteins, antibodies, enzymes, and peptides at large scale. It exposes web interfaces and APIs that run public…

Tamarind Bio provides scientists a no-code platform to design and optimize proteins, antibodies, enzymes, and peptides at large scale. It exposes web interfaces and APIs that run public…
What they do: No-code SaaS platform and API for large-scale computational protein design (AlphaFold, RFdiffusion, ProteinMPNN, GROMACS and 200+ models).
Customers: Life-science companies, biotechs, pharmaceutical researchers, and academic labs.
Funding: $13.6M total (includes $12M Series A led by Dimension Capital); prior Seed with Y Combinator participation.
Founded / HQ: Founded 2023; headquartered in San Francisco, California.
Computational protein design, antibody/peptide/enzyme engineering, structure prediction and high-throughput molecular-design workflows.
2023
Biotechnology
Crunchbase lists a Seed round on Apr 3, 2024 with Y Combinator and other investors.
$12,000,000
Company announced a $13.6M fundraise including a $12M Series A led by Dimension Capital.
“Participation from Y Combinator; Series A led by Dimension Capital with participation from other institutional investors (e.g., Eight Capital, Treeo VC listed as investors).”
About Tamarind Bio We enable any scientist to access AI-powered drug discovery. Thousands of scientists from large pharma companies, top biotechs, and academic institutions use Tamarind to design protein drugs, improve industrial enzymes, and create cutting edge molecules that weren’t feasible until now.
New AI models are quickly eclipsing physics-based tools in computational drug discovery. Scientists often struggle to fine-tune, deploy, and scale these models, leaving breakthroughs on the table. Tamarind provides a simple interface to the vast array of tools being released daily.
💻 About the Role We’re hiring a Computational Scientist to help curate, build, and scale Tamarind’s library of AI-powered drug discovery tools.
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In this role, you’ll work closely with the founders and engineering team to operationalize cutting-edge models for structure prediction, protein design, docking, scoring, and other core biological AI workloads. You’ll help transform fragmented research tools into production-ready workflows that scientists can run reliably at scale.
You’ll collaborate directly with customers to understand their discovery challenges and help them leverage Tamarind’s platform to run real biological AI pipelines. This often involves chaining multiple tools together, troubleshooting workflows, and identifying opportunities to improve the platform.
This role sits at the intersection of computational biology, machine learning, and scientific infrastructure , and is ideal for someone excited about applying the latest advances in AI to real-world drug discovery programs.
Our techstack:
Week in the Life:
Qualification requirements:
🧩 Our Interview Process
We keep our process focused, transparent, and designed to give both sides a clear sense of fit.
Compensation Range: $150K - $250K