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Salary
≈ $153k – $323k per year (Estimated)
Location
In office (San Francisco)
Visa
H-1B filings in 12 months: 1 · for this role: 1
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 16, 2026. First seen by Alion on May 11, 2026. Tamarind Bio scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Accelerate discovery with top computational biology tools on Tamarind Bio. Design and score proteins, peptides, small molecules and much more. Utilize top tools such as AlphaFold, RFdiffusion, BoltzGen, GROMACS or one of our 250+ other models.
Backed by Y Combinator

About Tamarind Bio

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.

About the Role

We’re hiring three exceptional Founding Software Engineers to help us scale the computational biology platform that powers our drug discovery pipeline.

In this role, you’ll collaborate closely with the founders to design, build, and scale our infrastructure, APIs, and web interface. You’ll own major pieces of our stack end-to-end - from architecture to deployment - and ship features that directly impact scientists and customers.

You’ll be responsible for maintaining and expanding the core systems that underpin our computational biology tooling, ensuring reliability, scalability, and performance as we grow.

This is a deeply collaborative and customer-facing role. You’ll work directly with users to understand their needs, translate feedback into product improvements, and deliver elegant solutions that accelerate their research.

Techstack:

  • Python, React, AWS (EC2, S3, DynamoDB), Docker, CUDA, Conda, TensorFlow/PyTorch; notebooks; bash/Slurm; APIs & web apps.

Week in the Life:

  • Partner with founders on product decisions, scope experiments, and ship quickly

  • Build/operate services (infra + ML + web) and iterate with customer feedback

  • Mix of coding, design reviews, and practical deployment work

  • Onsite expectation: Team currently onsite in SF ~5 days/week.

Ideal Qualifications:

  • Adaptability and openness to work on diverse problems (e.g. batch HPC scaling, frontend development, automated fine-tuning…)

  • AWS DevOps (DynamoDB, EC2, S3, docker, etc.) and MLOps (CUDA, Conda, Tensorflow, PyTorch)

  • Front-end development (React/Vercel)

  • Willingness to learn about biology-ML models

  • Located in the SF Bay Area or able to relocate to the Bay Area

Pluses:

  • Experience with AI/ML models across various architectures and environments

Technology

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.

Our Interview Process

We keep our process focused, transparent, and designed to give both sides a clear sense of fit.

1. Recruiter Screen (15-30 minutes) - Virtual

Meet with our recruiter to dive into your background, interests, and what you’re looking for next. We’ll also walk you through the company, team, and role.

2. Technical Interview (90 minutes) - Virtual

  • Co-Founder Interview (30 minutes): A conversation with Deniz Kavi (CEO & Co-founder) about product, collaboration, and how you approach building in an early-stage environment.

  • Technical Deep Dive (60 minutes): A live coding and problem-solving session with Sherry Liu (CTO & Co-founder) or a member of our engineering team.

3. Onsite (1 day) - San Francisco

Spend a day with us working on a mini project and meeting the team.

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