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BigHat Biosciences
Machine Learning Research Fellowship (12-18mo Fixed Term)

Machine Learning Research Fellowship (12-18mo Fixed Term)

Hybrid

San mateo, United states

Full Time

18-11-2025

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Skills

Communication Python Test Research Training Machine Learning PyTorch AWS Data Science

Job Specifications

Department: DS/ML (Data Science/Machine Learning)

Location: San Mateo, CA

Description

The Role: We are seeking talented, hard working associates to join our Machine Learning team for a fixed-term role.

At BigHat Biosciences, we’ve re-framed antibody drug development as an iterative, machine learning–driven, multi-objective optimization problem. Our roboticized high-throughput wet-lab continually adds to our large proprietary datasets, which are piped through a custom data management and orchestration layer to automatically update and deploy the latest models. This makes development of complex, net-gen therapeutics ‘trivially parallelizable’, at a pace which only accelerates as we develop better ML tooling.

As an ML Research Fellow you’ll work on developing novel ML models as well as helping with routine ML support of our ongoing therapeutics programs. Applications include multi-modal models of antibody biophysical properties, de novo and structure driven protein design, better protein language models, and active learning and bayesian optimization methods for embedding these models in our design-build-test loop, amongst many others. You’ll be mentored by an experienced ML scientist from our team and work closely with an interdisciplinary team of engineers, wet-lab scientists and drug developers to ensure your work is relevant for active drug development programs.

Key Responsibilities

Identify, evaluate, and deploy the right models and sequence engineering methods within our weekly antibody design-build-test workcell.
Develop and evaluate novel ML models or sequence optimization approaches to solve antibody engineering challenges relevant to BigHat’s therapeutics programs.
Support model building, active learning, and drug development efforts for ongoing BigHat partnerships.
Work with an interdisciplinary team of biologists, data scientists and machine learning scientists to gain sufficient domain familiarity to ensure your work is impactful.
Work within, and contribute to, a production-grade codebase and associated ML Ops infrastructure to maintain high levels of automation for existing and new models.
Document and present the results of your efforts to the relevant BigHat departments.

Skills Knowledge And Expertise

BS, MS, or PhD degree in ML, CS or in the hard sciences with significant ML experience and a strong math and prob/stats background.
Strong competency in Python, familiarity with PyTorch, exposure to modern software engineering best practices.
Strong communication skills, sufficient biomedical domain knowledge to interact effectively with diverse scientific teams.
Nice-to-haves include experience with protein structure modeling, de novo design, familiarity with antibody biology, and experience training and deploying models on AWS.

About the Company

BigHat’s mission is to improve human health by making it far easier to design advanced, next-generation antibody therapeutics. Our AI-enabled experimental platform integrates a high-speed characterization or “wet” lab with machine learning technologies to speed the antibody engineering process. When applied, these design capabilities have the potential to drive the development of new generations of safer and more effective treatments for patients suffering from today’s most challenging diseases. BigHat is backed by Section 3... Know more