Search the 7 jobs at Generate:Biomedicines

As a Senior Software Engineer, you will optimize infrastructure and workflows for machine learning and protein design, enforce best practices in containerization and CI/CD, and collaborate across teams to ensure scalable and robust systems.

The Senior Automation Engineer will lead lab automation efforts by designing and optimizing automated workflows, training junior engineers, and collaborating with scientists to enhance laboratory processes, particularly in molecular biology and protein characterization. The role focuses on integrating AI tools to boost lab efficiency and data quality for drug discovery.

The Principal Software Engineer will enhance the data curation and automation workflows within Generate's Digital team. Responsibilities include developing APIs, collaborating across teams to improve R&D workflows, ensuring system reliability, and integrating cutting-edge technologies, particularly generative AI and LLMs, into their software systems.

Director, Product Management role at Generate:Biomedicines, leading the development of a machine learning platform for novel therapeutics. Responsibilities include strategic roadmap development, new capability testing and launch, metric tracking, dataset acquisition, and competitive landscape analysis. Ideal candidate has 10+ years of AI/ML product management experience, proven strategy definition skills, and a Master's or PhD in Molecular Biology, Computer Science, Engineering, or related field.

The role involves developing generative models and algorithms for protein design, scaling systems for data utilization, collaborating with lab teams, and engineering ML systems for therapeutic applications.

The Senior Scientist in Machine Learning will develop generative models and algorithms for protein design, scale systems using GPU resources, and collaborate with both computational and wet lab teams to create new therapeutics. The role also involves engineering machine learning systems for large-scale applications and presenting research findings.

Interns will work on machine learning projects focusing on protein generative modeling, collaborate with mentors, and contribute to advancing technologies for therapeutic discovery. They will gain exposure to various scientific disciplines through cross-functional interactions and participate in the Computational Sciences Research Meeting.