A unified interface 300+ AI molecular design tools, available via web interface, API, and agents. Run models like AlphaFold, RFdiffusion, or BindCraft at massive scale, connect them together and fine-tune them on internal data. Backed by Y Combinator.
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 they're looking for
- Strong engineering fundamentals (Python preferred)
- Experience working with AI/ML systems or data pipelines
- Ability to operate in ambiguous, fast-moving environments
- Strong communication skills — able to interface with both technical and non-technical stakeholders
- Willingness to work onsite in San Francisco
More about this role
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.
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.
Work directly with customers (scientists, ML teams, pharma orgs) to understand workflows and translate needs into...
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