Product Management Lead

About the Team

We are a mission-driven group of scientists and engineers using cutting-edge computational methods to discover drugs for unmet medical needs. Our work spans machine learning, computational chemistry, biology, and wet lab experimentation, all operating within a high-trust, deeply technical environment. You’ll join a team with extremely strong ML talent that is actively pushing the frontier of AI in drug discovery. We are refining how experimental data, biological context, and computational models integrate into a seamless feedback loop. You will help reshape how data flows from experiment → infrastructure → model → decision and increase the speed and scale at which we learn.

Responsibilities

• Roadmap Ownership: Define, maintain, and communicate the technical and scientific product roadmap in alignment with company goals, ensuring prioritization of impactful projects.
• User research and design: Deeply understand user needs, translate workflow complexity into simple and effective product design.
• Team Collaboration and Translating Across Domains: Facilitate effective collaboration among software engineers, ML researchers, and computational chemistry scientists, acting as a glue to bridge technical and scientific perspectives.
• Stakeholder Engagement: Act as the primary point of contact for internal stakeholders, gathering input and communicating progress effectively.
• Data-Driven Decision Making: Leverage data and feedback to make informed decisions and iterate on product features.
• Product Strategy: Translate company objectives into actionable product plans, ensuring alignment with user needs and strategic goals.
• Execution Leadership: Drive projects from concept to completion, ensuring high-quality deliverables on time and within scope.
• Risk Management: Identify potential risks in product development and proactively implement mitigation strategies.

Qualifications

• 5+ years of product management experience in a technical or scientific environment.
• Bachelor’s degree in Computer Science, Engineering, Chemistry, or related field (advanced degree preferred).
• Strong understanding of machine learning systems and data infrastructure.
• Literacy in drug discovery, structural biology, or computational chemistry.
• Proven ability to operate at the interface of ML and life sciences.
• Demonstrated experience translating computational results into actionable scientific outcomes.
• Experience leading complex, cross-functional initiatives.
• Mindset: Passionate about innovation, problem-solving, and making a tangible impact on human health.
• Runs toward ambiguity rather than away from it.
• Knows what you don’t know and does not bluff in technical domains.
• Thinks in systems and anticipates what will not scale.
• Balances strategic thinking with hands-on execution.
• Motivated by advancing methods that impact real patients.

Skills

• Strong understanding of machine learning systems and data infrastructure.
• Literacy in drug discovery, structural biology, or computational chemistry.
• Proven ability to operate at the interface of ML and life sciences.
• Experience leading complex, cross-functional initiatives.
• Mindset: Passionate about innovation, problem-solving, and making a tangible impact on human health.

Benefits

Genesis Molecular AI is an inclusive workplace and an Equal Opportunity Employer. We are committed to fostering a diverse and inclusive environment where all employees feel valued and respected. We offer competitive compensation, comprehensive benefits, and opportunities for professional growth and development.

Pay

Competitive salary based on experience and qualifications.

Schedule

Full-time position.

About Genesis Molecular AI

Genesis Molecular AI is pioneering foundation models for molecular AI to unlock a new era of drug design and development. Our generative and predictive AI platform, GEMS (Genesis Exploration of Molecular Space), integrates AI and physics into industry-leading models to generate and optimize drug molecules, including the breakthrough generative diffusion model Pearl for structure prediction. Genesis is backed by premier AI and life science investors, including a16z, NVIDIA, Rock Springs Capital, Menlo Ventures, T. Rowe Price, Fidelity, and Radical Ventures. Genesis has also signed category-leading AI-pharma deals, the most recent of which was a significant expansion with Incyte (see coverage in Forbes and GEN) with a total potential deal value of several billion dollars. Genesis is headquartered in San Mateo, CA, with a fully integrated laboratory in San Diego.