Machine Learning Engineer

Join BigHat Biosciences, a pioneering company in AI-driven therapeutic antibody design. As a Machine Learning Engineer, 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 a true work-life balance.

• 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.
• Collaborate with interdisciplinary teams to ensure maximal efficiency in the automated deployment of the latest models and methods.

• Excellent communication skills, sufficient biomedical domain knowledge to interact effectively with diverse scientific teams
• Familiarity with the current state-of-the-art in ML-driven protein engineering
• 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
• Energy and ambition - ready to dive into a fast-paced environment and execute across multiple projects
• Masters in ML/CS/EE or Bachelors with 3+ years industry experience; hands on experience developing and applying novel ML methods and a strong quantitative background
• 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