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Senior Manager, Machine Learning Engineering - GenAI

Airbnb

Senior Manager, Machine Learning Engineering - GenAI

Airbnb

Gunnison, CO

·

On-site

·

Full-time

·

1mo ago

Compensation

$244,000 - $305,000

Benefits & Perks

Wellness benefits

Top Tier compensation with equity

Annual team offsites

Flexible PTO policy

Remote work flexibility

Learning and development stipend

Required Skills

PyTorch

Python

Apache Spark

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.

Your Expertise:

  • *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.
  • *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.

Your Location:

This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity. Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list. If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from.

How We'll Take Care of You:

Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

Pay Range

$244,000—$305,000 USD

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About Airbnb

Airbnb

An online community marketplace for people to list, discover, and book accommodations through mobile phones or the Internet.

5,001-10,000

Employees

San Francisco

Headquarters

$75B

Valuation

Reviews

4.2

9 reviews

Work Life Balance

4.2

Compensation

4.0

Culture

4.1

Career

3.0

Management

4.0

78%

Recommend to a Friend

Pros

Flexibility and work-life balance

Good pay and compensation

Great leadership and bosses

Cons

Dealing with difficult guests

Guest-related damages and messes

Stressful situations with complaints

Salary Ranges

16 data points

Junior/L3

L2

L3

L4

L5

L6

M3

M4

M5

M6

Mid/L4

Principal/L7

Senior/L5

Junior/L3 · Data Scientist L3

0 reports

$240,579

total / year

Base

-

Stock

-

Bonus

-

$204,492

$276,666

Interview Experience

9 interviews

Difficulty

3.4

/ 5

Duration

14-28 weeks

Offer Rate

44%

Experience

Positive 44%

Neutral 34%

Negative 22%

Interview Process

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

System Design Interview

5

Behavioral Interview

6

Onsite/Final Round

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Culture Fit