Level

Airbnb

Senior Machine Learning Engineer, Payments

AI in this role

pytorchtensorflow
prompt-engineeringai-agentsfine-tuningml-ops

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:

Payments is key for any healthy marketplace, and is just as central to our product at Airbnb. The Payments org at Airbnb is responsible for everything related to settling money in Airbnb’s global marketplace and makes the Payment experience as delightful, magical, intuitive, and easy as possible. At the Payments modeling team, our goal is to empower the mission by introducing intelligences and personalizations that optimize Airbnb’s massive daily transaction volume to best collect payments from guests, distribute payouts to hosts while preventing fraudulent transactions from happening.

The Difference You Will Make:

As a Senior ML Engineer for Payments, you will be the catalyst that transforms bold AI innovation -  LLMpowered workflow, realtime fraud defenses, and hyperpersonalized checkout flows -  into production systems that make Airbnb Payment experience feel effortless and secure; you’ll architect and own end-to-end solutions at global scale, partner closely with product, software, and operations teams to turn complex requirements into elegant, latencyfirst services, and set the technical standard for model governance, continuous learning, and engineering excellence that elevates our entire payments ecosystem while shaping the company’s broader AI strategy.

A Typical Day: 

  • Spearhead LLM agents, realtime anomaly detectors, and other breakthrough solutions that solve real-world problems and create product magic.
  • Collaborate with product, engineering, ops, and data science to spot high leverage opportunities, refine AI/ML requirements, make principled architecture choices, and measure business value with clear, data-driven metrics.
  • Design, train, deploy, and operate large-scale AI applications for both batch and streaming workloads, ensuring low latency, high reliability, and continuous improvement via automated monitoring and retraining loops.
  • Mentor and inspire teammates, fostering a collaborative, experimentation-driven environment where cutting edge research meets production excellence and every engineer is empowered to push AI boundaries at Airbnb.


Your Expertise:

  • 5+ years of industry experience in applied AI/ML, inclusive MS or PhD in relevant fields.
  • Strong programming (Python/Java) and data engineering skills.
  • Proven mastery of modern AI/LLM workflows — prompt engineering, fine tuning (LoRA, RLHF), hallucination mitigation, safety guardrails, and rigorous online/offline testing to minimize training/inference drift and ensure reliable outcomes.
  • Handson experience with at least three of the following: PyTorch/TensorFlow , scalable inference stacks, vector search, orchestration/MLOps platforms (Kubeflow, Airflow), largescale data streaming & processing (Spark, Ray, Kafka)
  • Demonstrated success designing, deploying, and monitoring production AI systems - e.g. personalization engines, generative content services - complete with drift/cost/latency monitoring, automated retraining triggers, and cross-functional collaboration that translates ambiguous business needs into measurable AI impact.
  • Prior knowledge of AI/ML Applications in the Payments domain is highly desirable

 

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.

Equal Employment Opportunity:

Airbnb values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Airbnb are considered without regard to race, color, religion, national origin, age, gender, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, gender expression, sexual orientation, or any other legally protected characteristic.

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$191,000—$223,000 USD

 

Reasonable Accommodations: We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.

A Note on Recruiting Scams: Scammers sometimes pose as Airbnb recruiters to get money or personal information from candidates. A few things that will always be true for Airbnb’s hiring process: our open roles are posted on Airbnb’s Career’s Page at careers.airbnb.com, and our recruiters correspond only from @airbnb.com or @ext.airbnb.com email addresses. Our recruiters will never ask for your Social Security number, bank account details, passport, or payment app information while you are interviewing.  We’ll also never ask you to pay a fee, send money, deposit or cash a check, or purchase work-related equipment (such as a company laptop) during the interview process. We encourage candidates to remain vigilant of these recruiting scams and not share sensitive information if you do not believe an individual is actually affiliated with Airbnb.

 

How we rate this

Senior Machine Learning Engineer, Payments at Airbnb rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Prompt EngineeringAI AgentsFine TuningML OpsPyTorchTensorFlow

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. How do you decide when an AI agent can act on its own versus asking for approval first?
  3. Walk me through fine-tuning a model: what data did you use, and how did you check the result?
  4. How do you monitor a model once it's live, and how do you know it needs retraining?
  5. Walk me through how you've used PyTorch in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Prompt Engineering, AI Agents, Fine Tuning, ML Ops, and PyTorch. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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