Tamarind Bio Series A

Forward Deployed Engineer

San Francisco, CA On-site $102K-$182K Added Jun 28

About the role

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. FORWARD DEPLOYED ENGINEER ABOUT THE ROLE We’re hiring a Forward Deployed Engineer — one of the highest-leverage roles on the team. You’ll sit at the intersection of engineering, product, and customers — working directly with scientists, ML teams, and pharma stakeholders to deploy Tamarind into real-world workflows. This role owns the full arc: from first technical conversation → pilot → production deployment. Every deployment becomes a product signal, a reference customer, and a revenue driver. The customer relationship moves at the speed you move. WHAT YOU’LL DO - Work directly with customers (scientists, ML teams, pharma orgs) to understand workflows and translate needs into deployable solutions - Stand up AI/ML workflows using Tamarind’s platform — often within days of initial engagement - Configure and deploy models (e.g.

Industry

AI / Computational Biology & Drug Discovery

Top skills for this role

  • Computational biology domain knowledge (protein engineering
  • drug discovery AI)
  • 2. Customer-facing technical integration with pharma and biotech research teams
  • 3. AI platform deployment and configuration for scientific workflows

Languages

not specified (Python likely given computational biology context)

Frameworks & tools

Tamarind Bio platform APIAlphaFold/RFdiffusion/MPNN/GROMACS toolchain integrationscientific data pipelines

AI / ML skills

AI-powered drug discovery platform deployment and configurationstructure prediction and protein design AI methodscomputational biology AI model orchestration

Customer skills

Direct collaboration with bench scientists, ML teams, and pharma stakeholders; translating wet-lab and computational workflows into platform integrations; building trusted scientific relationships

Domain knowledge

Computational biology; drug discovery; protein engineering; structure prediction; pharma/biotech R&D workflows; SOC 2/enterprise security in life sciences

Travel: not specified (in-person SF implied)
Equity: not specified (Founding role; equity implied)

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