Senior Manager, Machine Learning Engineering - GenAI

Airbnb•Village of Kings Point, NY

21d•Remote

About The Position

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join The Community Support Platform (CSP) at Airbnb is a critical system that drives our customer support operations. CSP empowers Airbnb's global network of Community Support ambassadors, utilizing cutting-edge technology to deliver exceptional customer service with high efficiency. As part of the CSP vision, we are harnessing AI to revolutionize Airbnb’s approach to customer service. Our AI Product team is focused on providing a seamless user experience by combining AI capabilities with the expertise of our support ambassadors. The Difference You Will Make: Lead and Mentor: Guide a dynamic team of highly skilled applied scientists and machine learning engineers in the research, design and optimization of AI models and services. Strategize and Innovate: Develop and refine the overarching strategy for the ML and AI aspects of our community support products, focusing on scalability, quality, safety, performance, and reliability. Drive Excellence: Foster rapid development cycles without sacrificing quality, collaborating closely with platform, backend, and frontend engineers to engineer robust ML models and systems that enhance community support initiatives. Make Data-Driven Decisions: Evaluate technical trade-offs in key decisions, ensuring optimal outcomes through data-backed strategies. Uphold Technical Standards: Conduct thorough design and architecture reviews to continually elevate our standards of technical excellence.

Requirements

Expertise in ML & AI: Deep knowledge of various machine learning and AI methodologies, including LLMs and non-LLMs, tailored for user-facing products.
Leadership in ML Development: Proven experience in leading teams that develop large-scale ML models and systems to improve online user experiences.
Management and Mentorship: Strong leadership skills with a track record of nurturing an innovative and collaborative team environment.
Communication Excellence: Exceptional verbal and written communication abilities, with a keen eye for detail.
Collaborative Spirit: Demonstrated capability to work effectively with stakeholders at all organizational levels, both internally and externally.
Problem Solving: Skilled in navigating and resolving ambiguous challenges through proactive and strategic approaches.
Educational Background: PhD, or Master's degree in Computer Science, Mathematics, Statistics, or related technical field.
Industry Experience: 10+ years of experience in building and shipping AI models and products, including 2+ years of experience with LLMs.
Leadership Experience: 5+ years managing machine learning teams that deliver large impact.

Nice To Haves

Technical Proficiency: Expert knowledge of machine learning algorithms and techniques.
Customer Support Systems: Experience with AI technologies in customer support applications.
Advanced LLM Expertise: Experience with LLM alignment techniques (SFT, RLHF, DPO, etc) and LLM evaluation.
Infrastructure Acumen: Background in working with ML infrastructures and complex system designs.
Continuous Learner: Ability to absorb new concepts quickly and integrate them effectively into business processes.

Responsibilities

Lead and Mentor: Guide a dynamic team of highly skilled applied scientists and machine learning engineers in the research, design and optimization of AI models and services.
Strategize and Innovate: Develop and refine the overarching strategy for the ML and AI aspects of our community support products, focusing on scalability, quality, safety, performance, and reliability.
Drive Excellence: Foster rapid development cycles without sacrificing quality, collaborating closely with platform, backend, and frontend engineers to engineer robust ML models and systems that enhance community support initiatives.
Make Data-Driven Decisions: Evaluate technical trade-offs in key decisions, ensuring optimal outcomes through data-backed strategies.
Uphold Technical Standards: Conduct thorough design and architecture reviews to continually elevate our standards of technical excellence.