Product Owner for ML Interface Solutions

Role Summary

Product Owner for ML Interface Solutions, based in Cambridge, MA. Responsible for bridging AI/ML model outputs with scientists, owning the roadmap and backlog for front-end interfaces that enable Large Molecule Research (LMR) scientists to access, interpret, and act on ML predictions within biologics discovery workflows. Works in agile pods with data scientists, ML engineers, UX/UI designers, and scientists to deliver user-centered solutions that accelerate adoption and improve decision making.

Responsibilities

• Own and prioritize the product roadmap and backlog for ML interface solutions serving LMR scientists
• Partner with data scientists and ML engineers to deeply understand model outputs, capabilities, and limitations to effectively support scientists on decision making
• Design and deliver intuitive front-end interfaces that make ML predictions accessible, interpretable, and actionable for bench scientists
• Define detailed user stories, acceptance criteria, and success metrics for interface features based on scientific workflows
• Lead agile development with UX/UI designers, front-end developers, and data engineers to deliver iterative improvements
• Establish frequent touchpoints with software development and MLOps teams to validate technical requirements and architectural elements necessary for optimal performance of ML solutions
• Ensure interfaces properly communicate model uncertainty, confidence levels, and appropriate scientific context
• Balance new feature development with technical debt and user feedback

Qualifications

• Required: Bachelor Degree with significant industry experience in computational biology (antibody discovery, protein design, large molecules or related topic). MS or PhD preferred.
• Experience: 5+ years of experience in product management and translating business requirements to technical specifications
• Proven track record collaborating with data scientists and developers in a scientific environment
• Experience delivering digital products with intuitive interfaces and effective data visualizations

Skills

• Solid understanding of biologics discovery workflows and antibody/protein engineering challenges
• Ability to translate complex concepts into intuitive user experiences and compelling visualizations
• Experience with agile product development methodologies and cross-functional teams
• Familiarity with ML/AI applications in drug discovery and interpretation of model outputs
• Change management skills to drive adoption of new tools and workflows
• Experience with design and collaboration tools such as Figma, Miro, JIRA
• Ability to balance competing priorities and make data-driven decisions on feature prioritization
• Curiosity about emerging technologies in AI/ML and scientific computing

Education

• Bachelor Degree required with significant industry experience in computational biology (antibody discovery, protein design, large molecules or related topic). MS or PhD preferred.