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
- Fullstack experience across backend, infra, and frontend
- Strong proficiency in Python and React
- Experience with AWS DevOps (EC2, S3, DynamoDB, Docker) and/or MLOps (CUDA, TensorFlow, PyTorch, Conda)
- Adaptability to work on diverse problems (batch HPC scaling, frontend dev, automated fine-tuning, etc.)
- Experience with AI/ML model deployment across various architectures and environments
- Familiarity with computational biology or ML for scientific applications
- Python, React, AWS (EC2, S3, DynamoDB), Docker, CUDA, Conda, TensorFlow/PyTorch; notebooks; bash/Slurm; APIs & web apps.
Responsibilities
- Build and operate services (infra + ML + web) while iterating with customer feedback
- Mix of coding, design reviews, and practical deployment work
- Partner with founders on product decisions, scope experiments, and ship quickly
- Design, build, and scale our infrastructure, APIs, and web interface
- Own key parts of our stack end-to-end — from architecture to deployment — and ship features that directly impact scientists and customers
- scaling ML inference on AWS across hundreds of GPUs
- parsing pdb files with Biopython
Other
- Contract role through the end of January 2026
- Remote within the U.S. (up to 40 hours per week)
- Collaborate closely with a small, mission-driven team
- Collaborate closely with the team working onsite in SF (Pacific Time hours preferred)
- U.S.-based and available to work up to 40 hours per week through January
