Lead AI Scientist

At Gen, we are scrappy and relentlessly customer driven. We create room for healthy debate, experimentation and continuous learning, and we seek out people with different experiences, identities and ideas to join our team. You’ll work with people who back each other, respect each other and understand that our differences are a competitive advantage.

If this sounds like you, we’d love you to be part of Gen.

About the Role

We are looking for a Manager to lead a team building and scaling machine learning and AI solutions that drive measurable business impact. This role is designed for someone who is passionate about applied machine learning, artificial intelligence, and using data-driven solutions to solve real-world problems.

As a Manager, Machine Learning & AI, you will combine people leadership, technical direction, and cross-functional execution to bring machine learning and AI solutions from experimentation into production. You will help shape the team’s roadmap, guide technical decision-making, and work closely with Product, Engineering, Data, and platform partners to deliver solutions that are scalable, reliable, and valuable to the business.

This role is well suited for someone who enjoys leading teams while staying close enough to the work to influence architecture, execution quality, and engineering standards. You should be comfortable translating ambiguous business problems into practical machine learning and AI opportunities, and helping a team deliver them end to end.

Key Responsibilities

Lead, coach, and develop a high-performing machine learning and AI team, fostering a culture of ownership, technical excellence, and continuous learning.

Shape the technical direction of machine learning and AI initiatives aligned with business priorities and product goals.

Partner closely with Product, Engineering, Data, and platform teams to frame business problems and translate them into machine learning and AI solutions.

Guide projects from early exploration and experimentation through development, production, monitoring, and iteration.

Drive strong standards in experimentation, model evaluation, reliability, maintainability, monitoring, and governance across the team’s work.

Support the team in designing scalable machine learning systems, workflows, and development practices that improve long-term delivery velocity.

Provide technical guidance on architecture, trade-offs, and implementation strategy without becoming a bottleneck for the team.

Communicate technical concepts, risks, and opportunities clearly to both technical and non-technical stakeholders.

Research, evaluate, and guide the practical adoption of new machine learning and AI ideas, including modern methods such as LLM-based systems, where they can create meaningful business value.

Help build repeatable capabilities, frameworks, and ways of working that enable multiple machine learning efforts to succeed over time, not just individual one-off projects.

About You

Demonstrated experience leading machine learning or AI initiatives from idea to production, with a track record of translating business problems into practical solutions.

Experience managing, mentoring, and developing technical team members.

Strong foundation in machine learning, experimentation, statistical thinking, and software engineering.

Good programming knowledge and strong hands-on familiarity with Python and SQL.

Experience developing, deploying, and operating machine learning systems in production.

Ability to frame business problems, prioritize effectively, and guide teams toward practical, high-impact solutions.

Strong communication and collaboration skills, with the ability to work effectively across technical and non-technical stakeholders.

Comfortable operating in fast-paced and ambiguous environments while balancing execution, technical quality, and team growth.

Experience working with modern machine learning frameworks and tooling, with the ability to evaluate and apply the right technologies for different use cases.

Familiarity with modern MLOps tooling and production workflows, including model monitoring, CI/CD, and lifecycle management.

Experience with cloud platforms and production infrastructure.

Exposure to natural language processing, search, recommendation systems, or modern GenAI / LLM application patterns is a plus.

Experience improving engineering standards, governance, and reusable internal capabilities across multiple machine learning projects.

What's Next...

Screening Call

Take Home Assessment

Hiring Manager Interview

Stakeholder Chat