BigHat Biosciences

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 32, Andreessen Horowitz, 8VC, Amgen Ventures, Bristol Myers Squibb, Quadrille, Grids Capital, AME Cloud Ventures, Innovation Endeavors and Gaingels.

Listed Jobs

Company Name

BigHat Biosciences

Job Title

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

Job Description

Job Title: Machine Learning Research Fellow (12‑18 month Fixed Term) Role Summary A research fellow in machine learning focused on antibody drug development. The role involves designing, building, and deploying advanced ML models (multi‑modal, sequence optimization, protein language models) to accelerate antibody design within a rapid design‑build‑test‑learn cycle. The fellow will collaborate closely with cross‑functional teams of biologists, engineers, and data scientists to translate machine learning solutions into actionable drug‑development outcomes. Expectations - Deliver novel machine‑learning algorithms and sequence‑engineering methods tailored to antibody engineering challenges. - Provide ongoing ML support for active therapeutics programs, including model training, evaluation, and deployment. - Integrate research findings into production‑grade codebases and ML‑Ops pipelines, ensuring robust automation. - Communicate results clearly to scientific peers and stakeholders. - Exhibit a strong foundation in mathematics, statistics, and computer science, and adapt quickly to evolving biotechnology domains. Key Responsibilities - Identify, evaluate, and deploy suitable ML models and sequence‑engineering techniques for weekly antibody design‑build‑test cycles. - Research and implement cutting‑edge methods such as active learning, Bayesian optimization, and protein design models. - Collaborate with biologists, data scientists, and ML engineers to align model development with drug‑development objectives. - Contribute to a production‑grade codebase, maintaining code quality, documentation, and adherence to ML‑Ops best practices. - Document methodologies, performance metrics, and insights; present findings to cross‑functional teams. Required Skills - Proficiency in Python; strong experience with PyTorch or equivalent deep‑learning frameworks. - Solid background in probability, statistics, and machine‑learning theory. - Familiarity with modern software engineering practices (version control, testing, CI/CD). - Excellent written and verbal communication; ability to translate complex technical concepts for interdisciplinary audiences. - Preferred: knowledge of protein structure modeling, de novo design, antibody biology; experience deploying models on cloud platforms (AWS or equivalent). Required Education & Certifications - BS, MS, or PhD in Machine Learning, Computer Science, Bioinformatics, Computational Biology, or related hard science disciplines. - Demonstrated significant ML experience through research projects, publications, or industry work. - No mandatory certifications, but cloud or ML‑Ops certifications are advantageous.

San mateo, United states

Hybrid

18-11-2025

Company Name

BigHat Biosciences

Job Title

Software Engineer (SWE I / SWE II)

Job Description

Job Title: Software Engineer (SWE I / SWE II) Role Summary: Design, implement, test, and maintain features for BigHat’s cloud‑based LIMS+ platform that supports therapeutic antibody development. The role involves working independently on well‑scoped features, collaborating closely with scientists, product owners, and engineers, and owning quality from development through production. Expectations: - 3–5 years of production software experience, or 2+ years with biotech/life‑sciences or laboratory software background. - Proven ownership of end‑to‑end development, testing, and release cycles in a production environment. - Ability to translate laboratory workflows into reliable software solutions. - Strong communication of progress, risks, and trade‑offs, and effective collaboration across cross‑functional teams. Key Responsibilities: - Design, code, test, and deploy features in the LIMS+ platform. - Work independently on small‑to‑medium scope tasks, managing end‑to‑end delivery. - Collaborate with scientists, product owners, and fellow engineers to map real‑world lab processes to software requirements. - Participate in engineering ceremonies, technical discussions, and code reviews. - Own debugging, test failure resolution, and production incident handling. - Continuously deepen technical knowledge of the codebase, infrastructure, and supporting systems. Required Skills: - Front‑end: TypeScript, React, Material‑UI, Vega. - Back‑end: Python 3, SQLAlchemy, RESTful API design. - Cloud: AWS (CDK, Lambda, Step Functions, ECS/Batch, Fargate, API Gateway, Athena). - Databases: Relational (PostgreSQL) and experience with Pandas. - Development practices: Automated testing, code review, debugging, and production monitoring. - Strong communication, independent problem solving, and collaborative mindset. Required Education & Certifications: - Bachelor’s degree in Computer Science, Software Engineering, or a related field (or equivalent professional experience).

San mateo, United states

Hybrid

Junior

21-01-2026