Machine Learning Scientist
BigHat Biosciences
- San Mateo, United States
- Mid Level
- PhD or doctorate
- Posted
Skills
Required
- ML
- ML-driven protein engineering
- Python
- PyTorch
- agentic/LLM-assisted coding
- CI/CD
- novo design
- NGS data
- Bayesian optimization
Preferred
- antibody sequence and structure
- predictive models
- antibody properties
- multi-objective iterative protein sequence optimization
- lab-in-the-loop antibody design problems
About BigHat Biosciences
Join BigHat Biosciences, a pioneering company in AI-driven therapeutic antibody design. As a Machine Learning Scientist, you will advance the state of the art in ML-driven therapeutic antibody design, contribute to the development of new drugs, and collaborate with an interdisciplinary team of drug developers, wet lab scientists, automation specialists, and data scientists. Enjoy a culture of excellence and growth, swift promotions, autonomy, fair compensation, and true work-life balance.
Collaborate with an interdisciplinary team of drug developers, wet lab scientists, automation specialists, data scientists, etc. to ensure maximal efficiency in the automated deployment of models and methods.
Responsibilities
- Design and implement state-of-the-art generative models of antibody sequence and structure, and predictive models of antibody properties.
- Develop multi-modality, multi-objective iterative protein sequence optimization approaches to lab-in-the-loop antibody design problems.
Requirements
- Familiarity with the current state-of-the-art in ML-driven protein engineering
- Strong competency in Python, familiarity with PyTorch (even without LLMs!) and experience with modern software engineering best practices, including not just agentic/LLM-assisted coding but testing, CI/CD, etc
- Energy and ambition - ready to dive into a fast-paced environment and execute across multiple projects
- PhD in ML/CS/EE or relevant scientific discipline, hands on experience developing and applying novel ML methods and a strong quantitative background
- Nice-to-haves include experience with de novo design, NGS data, Bayesian optimization, familiarity with antibody biology and drug development, experience training and deploying models on AWS, and publications at major ML conferences
- Excellent communication skills, sufficient biomedical domain knowledge to interact effectively with diverse scientific teams
Pay
USD 150,000 - 200,000
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