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.

As an Applications Scientist at Tamarind, you’ll guide customers in using state-of-the art molecular design tools, provide strategic scientific support, and produce educational content for scientists’ benefit.

What you’ll do:

• Provide scientific support to existing and prospective customers, focusing on practical applications of molecular AI in therapeutic programs.
• Write high quality educational content for tens of thousands of scientists’ consumption
• Publish and present at scientific conferences
• Troubleshoot customer pipelines, tickets, tool use problems

Qualifications:

• PhD in computational chemistry, bioinformatics, structural biology, biophysics or a related field
• Expertise in the application of machine learning methods for small molecule design, especially as applied to therapeutic programs
• Programming skills with fluency in manipulating biological data such as molecular structures, compounds, sequences, and databases
• Willingness to travel for conferences and customer on-site visits

Our technology sits at the intersection of DevOps, MLOps, and Computational Biology. We deal with problems ranging from scaling ML inference on AWS for hundreds of GPUs to dissecting pdb files with Biopython. We deploy a wide range of open source ML models for customers, navigating between Docker containers, Colab notebooks, bash scripts, slurm jobs, and more.