Lead AI Scientist, Manager - MoneyLion
Skills
About the Role
You will lead, coach, and develop a high-performing machine learning and AI team, fostering ownership, technical excellence, and continuous learning. You'll shape the technical direction of machine learning and AI initiatives aligned with business priorities and product goals, and partner closely with Product, Engineering, Data, and platform teams to translate business problems into ML and AI solutions. You'll guide projects from early exploration through production, monitoring, and iteration, drive strong standards in experimentation, model evaluation, reliability, and governance, and provide technical guidance on architecture and implementation strategy without becoming a bottleneck. You'll also research and guide adoption of new ML and AI ideas, including LLM-based systems, and help build repeatable frameworks that enable multiple ML efforts to succeed over time.
Requirements
- Demonstrated experience leading machine learning or AI initiatives from idea to production
- 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 solutions
- Strong communication and collaboration skills
- Comfortable operating in fast-paced and ambiguous environments
- Experience working with modern machine learning frameworks and tooling
- 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
Responsibilities
- Lead, coach, and develop a high-performing machine learning and AI team
- 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
- Support the team in designing scalable machine learning systems, workflows, and development practices
- Provide technical guidance on architecture, trade-offs, and implementation strategy
- Communicate technical concepts, risks, and opportunities clearly to technical and non-technical stakeholders
- Research, evaluate, and guide the practical adoption of new machine learning and AI ideas, including LLM-based systems
- Help build repeatable capabilities, frameworks, and ways of working that enable multiple machine learning efforts to succeed