Synced from Greenhouse · Jun 23

Machine Learning Engineer

AirbnbRemote-USAPosted Jun 23, 2026
Machine Learning EngineerRemoteSenior
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Mirrored from Airbnb's own Greenhouse careers system · refreshed hourly

$196k–$227k
Compensation
167
Other open Airbnb roles
Jun 23
Posted
Greenhouse
Applicant system
Job descriptionReq 8014904

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:

Machine Learning and Artificial Intelligence are at the heart of the Airbnb product. From Trust to Payments, and from Customer Service to Marketing we rely on ML to ensure that guests and hosts have the best possible experience with Airbnb. 

Our ML team in Assistance Engineering is the team responsible for adopting the Agentic AI technologies to enable an intelligent, scalable and exceptional customer service experience. We are responsible for developing the Chat AI assistant, Voice AI Assistant and Human agent Assistant! The team is constantly exploring the SOTA Agentic architecture, develops and enhances various AI models, ML services and leverages tools including SFT, Reinforcement learning, Distillation, RAG/Search,  LLM evaluation and testing automation, feedback-based learning and guardrail for a wide range of applications in Airbnb.

The Difference You Will Make:

We believe our current customer experiences in these domains are only scratching the surface of the innovations that are possible, and that science is at the heart of delivering a step-function change for our Guest and and Host on Airbnb. 

You will build and leverage cutting edge AI technologies to transform Airbnb’s customer service by delivering personalized, easy-to-use and proactive customer service experience. 

Many of the initiatives you’ll tackle are in their early conceptual stages. You will have the opportunity to shape these ideas from inception to production, turning visionary concepts into impactful realities.

A Typical Day: 

  • Champion the development of novel ML systems, product integrations, and performance optimizations to solve real-world problems
  • Work cross-functionally with product, design, and other engineering counterparts to design and build efficient AI solutions for Airbnb CS products
  • Learn and share the latest AI/ML technologies with the team.


Your Expertise:

  • PhD or Master's degree w/ 6+ YOE in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field — or equivalent industry experience
  • Hands-on expertise in LLM, including pretraining, fine-tuning (SFT, RLHF, GRPO), prompt engineering, RAG architectures, and LLM evaluation frameworks
  • Experience building Agentic AI systems — including multi-agent orchestration, tool-use, planning, memory, and autonomous reasoning pipelines (e.g., ReAct, LangGraph, AutoGen, or similar)
  • Experience of shipping production-grade ML/AI systems at scale, with deep understanding of ML infrastructure, model serving, and MLOps best practices
  • Excellent communication skills with the ability to collaborate effectively across Engineering, Product, and Design organizations

 

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.

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: reasonableaccommodations@airbnb.com. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process. 

We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application.

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
$196,000$227,000 USD
View original posting on Greenhouse

What applying to Airbnb usually looks like

Based on publicly available information, candidates applying through greenhouse for roles at Airbnb can typically expect an initial application review followed by a recruiter screen to discuss background and role fit. The process may include multiple stages such as hiring manager conversations, functional or role-specific assessments, and panel interviews with team members, depending on the position, whether technical like software-engineer or data-engineer, or non-technical like account-manager or marketing-manager. Take-home exercises or case studies are common for design, analytics, and product-oriented roles. Communication is generally handled through the Greenhouse platform, with updates sent via email or an online portal. Response times vary and candidates should not assume a fixed timeline. Overall, applicants can generally expect a structured, multi-step evaluation process consistent with common industry practices for companies using this applicant tracking system.

Based on publicly available information. LandEarly does not verify interview process details.

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Machine Learning Engineer
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