Machine Learning Engineering Manager, Technical Lead

2 weeks ago


Seattle, Washington, United States Stripe Full time
About Stripe

Stripe is a leading financial infrastructure platform for businesses, providing a range of services to help companies grow their revenue and accelerate new business opportunities.

We are a mission-driven company, aiming to increase the GDP of the internet and make the global economy more accessible to everyone.

About The Team

The Stripe Assistant team is a newly formed group of talented engineers and researchers working together to build an intelligent assistant for all merchants who use Stripe.

We are developing cutting-edge AI/ML systems, including RAG-based systems and fine-tuned models, to automate tasks, assist users, and resolve issues.

Key Responsibilities
  1. Drive AI/ML Vision: Develop and implement an ambitious vision for AI/ML that benefits our users and drives business growth.
  2. Technical Leadership: Set the technical direction for the team, aligning with business goals and ensuring the delivery of high-quality ML systems.
  3. Product Integration: Collaborate with partner teams to brainstorm and coordinate product integrations, driving innovation and growth.
  4. Prototype Development: Propose new ideas and build prototypes to test and validate concepts.
  5. Community Engagement: Be an integral part of a larger ML community, both internally and externally, sharing knowledge and best practices.
  6. Team Management: Hire, develop, and lead a world-class team of ML engineers, ensuring their growth and success.
  7. Coach and Mentor: Coach engineers to help them grow in their careers, maintain a high bar, and deliver exceptional results.
Requirements
  1. ML Team Leadership: Have at least 5 years of experience managing ML teams, with a proven track record of success.
  2. High-Growth Environment: Lead by example in high-growth, high-impact environments, demonstrating adaptability and resilience.
  3. ML System Development: Have experience building and shipping ML systems, with a focus on user experience and production readiness.
  4. User Experience: Enjoy measuring and improving user experience, with a passion for delivering exceptional results.
  5. Production Systems: Hold yourself and others to a high bar when working with production systems, ensuring reliability and scalability.
  6. Collaboration: Thrive in a collaborative cross-functional environment, working effectively with diverse teams.
Preferred Qualifications
  1. LLM and RAG Experience: Have experience shipping LLM and RAG systems, with a deep understanding of their applications and limitations.


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