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 looking for an AI Software Engineer to lead the development of AI-enabled workflows across our platform. You'll be responsible for expanding our copilot for computational biology to improve its reliability and capabilities. You’ll develop complex and scalable workflows for planning and executing pipelines, data analysis, and simulation for biotech and large pharma researchers. You’ll work closely with the founders and researchers to tailor your solution to customer needs.

You should thrive in a fast-paced startup environment where you'll wear multiple hats, learn new technologies quickly, and help solve novel technical challenges. We value engineering judgment, problem-solving ability, and the capacity to build systems that can evolve with our growing needs.

Ideal Qualifications:

• Prompt engineering and finetuning for LLMs
• Build and own end-to-end scalable AI systems, support hundreds of tenants, and operate at scale in production
• Front-end development (React/Next.js)
• Located in the SF Bay Area or able to relocate to the Bay Area

Pluses:

• Familiarity with cloud infrastructure
• DevOps/MLops (Docker, Conda, Kubernetes)

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.