Product Owner for ML Interface Solutions

Role Summary

Product Owner for ML Interface Solutions in Cambridge, MA. Bridges AI/ML models and scientists in Large Molecule Research, building intuitive front-end interfaces that translate ML outputs into actionable visualizations for biologics discovery. Owns the product roadmap and backlog, collaborating with data scientists, ML engineers, and bench scientists to accelerate antibody discovery and protein engineering.

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

Skills

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

Education

• Bachelor’s degree in computational biology or related field; MS or PhD preferred