What are the responsibilities and job description for the Software Engineer position at Tamarind Bio?
We’re hiring 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.
Ideal Qualifications
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.
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.
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, K8s, etc.) and MLOps (CUDA, Conda, Tensorflow, PyTorch)
- Fullstack development
- Located in the SF Bay Area or able to relocate to the Bay Area
- Experience with AI/ML models across various architectures and environments
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.