BigHat Biosciences Tech Stack

AI-guided antibody design platform integrating wet-lab automation with machine learning

Biotechnology Research San Mateo, California 51–200 employees Founded 2019 Privately Held

BigHat Biosciences operates a hybrid wet-lab and computational platform for antibody engineering, combining high-throughput automation (OpenTrons, Tecan, Batch processing) with machine learning (PyTorch, generative models). The tech stack reveals a maturing infrastructure—LIMS, PostgreSQL, AWS orchestration via Step Functions and ECS—built to handle iterative design cycles. Active projects span de novo design methods, antibody property prediction, and cloud-based LIMS expansion, while hiring across research, data, and engineering roles signals scaling pressure on both experimental throughput and computational performance.

Tech Stack 21 technologies

Core StackTypeScript React Python AWS AWS Lambda PostgreSQL Pandas PyTorch LIMS Material-UI Vega SQLAlchemy AWS CDK AWS Step Functions AWS ECS Batch AWS Fargate API Gateway Athena OpenTrons Tecan

What BigHat Biosciences Is Building

◆Challenges

Expanding antibody discovery capabilities
Scaling therapeutic antibody production
Scaling up high-throughput platform
Optimizing platform performance
Improving production workflows

▲Active Projects

Generative models of antibody sequence and structure
Predictive models of antibody properties
De novo design methods for initial hits
Display-based selection campaigns
Antibody library design and optimization
Cloud-based lims+ platform
Scaling up high-throughput platform
In-house reagent manufacturing
Performance optimization experiments
Characterization of lead therapeutic candidates

Hiring Activity

Accelerating5 roles · 4 in 30d

Department

Research

Data

Engineering

Seniority

Director

Junior

Mid

Principal

Senior

Company intelligence

Find more companies like BigHat Biosciences by tech stack, pain points and active projects

Get started free

About BigHat Biosciences

BigHat Biosciences designs advanced antibody therapeutics using an AI-enabled platform that combines rapid lab characterization with machine learning. Founded in 2019 and based in San Mateo, the company employs 51–200 people and is backed by Section 32, Andreessen Horowitz, 8VC, Amgen Ventures, Bristol Myers Squibb, Quadrille, Grids Capital, AME Cloud Ventures, Innovation Endeavors, and Gaingels. The platform integrates wet-lab automation (OpenTrons, Tecan instruments) with computational design tools to accelerate antibody engineering—reducing the time and cost of discovering next-generation therapeutics. Current work includes generative sequence-structure models, predictive property models, display-based selection, and scaling production workflows.

HeadquartersSan Mateo, California

Company Size51–200 employees

Founded2019

Hiring MarketsUnited States

Frequently Asked Questions

What tech stack does BigHat Biosciences use?

Python, PyTorch, TypeScript/React, PostgreSQL, LIMS, AWS (Lambda, Step Functions, ECS, Fargate, Batch, Athena), Pandas, SQLAlchemy, OpenTrons, and Tecan. The stack emphasizes workflow orchestration and data pipeline automation.

What is BigHat Biosciences working on?

Generative models for antibody sequences and structures, predictive models of antibody properties, de novo design methods, display-based selection campaigns, antibody library optimization, cloud-based LIMS platform, and scaling high-throughput characterization and production workflows.

How this profile is built

BigHat Biosciences's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →

This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.