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.
Requirements
- Python
- React
- Deep Learning
- Bash/Shell
- Amazon Web Services (AWS)
- AWS DevOps (DynamoDB, EC2, S3, docker, etc.) and MLOps (CUDA, Conda, Tensorflow, PyTorch)
- Front-end development (React/Vercel)
Responsibilities
- maintaining and expanding the core infrastructure that powers our drug discovery software
- design, build, and scale our web interface and API products
- scaling ML inference on AWS for hundreds of GPUs
- dissecting pdb files with Biopython
- deploy a wide range of open source ML models for customers
- navigating between Docker containers, Colab notebooks, bash scripts, slurm jobs, and more
Other
- Interacting directly with customers is a highly important component of this job.
- build products around customer needs, taking full ownership over serving their requests.
- Adaptability and openness to work on diverse problems (e.g. batch HPC scaling, frontend development, automated fine-tuning…)
- Willingness to learn about biology-ML models
- Located in the SF Bay Area or able to relocate to the Bay Area
