Learning Experience Lx Content Designer jobs at Airbnb

The Difference You Will Make:

Our team pushes the boundaries of AI and machine learning throughout the search ranking stack, from data pipelines to feature engineering, model innovation, real-time serving, and large-scale experimentation. You’ll work hands-on with diverse data sources—structured, behavioral, image, and text—transforming raw information into intelligent signals that drive relevance and personalized recommendations.

A Typical Day:

• Work with large scale structured and unstructured data, build and continuously improve cutting edge Machine Learning (ML) models for Airbnb product, business and operational use cases.
• Work collaboratively with cross-functional partners including software engineers, product managers, operations and data scientists, identify opportunities for business impact, understand, refine, and prioritize requirements for machine learning models, drive engineering decisions, and quantify impact.
• Hands-on develop, productionize, and operate ML/AI models and pipelines at scale, including both batch and real-time use cases.
• Leverage third-party and in-house ML/AI tools & infrastructure to develop reusable, highly differentiating and high-performing Machine Learning systems, enable fast model development, low-latency serving and ease of model quality upkeep.
• Example projects include: feature platform, model interpretability, hyperparameter optimization, concept drift detection.

Your Expertise:

• 12+ years of industry experience in applied ML/AI, inclusive MS or PhD in relevant fields.
• Strong programming (Scala / Python / Java / C++ or equivalent) and data engineering skills.
• Deep understanding of ML/AI best practices (e.g. training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (e.g. neural networks/deep learning, optimization) and domains (e.g. natural language processing, computer vision, personalization, search and recommendation, marketplace optimization, anomaly detection).
• Experience with 3 or more of these technologies: Tensorflow, PyTorch, Kubernetes, Spark, Airflow (or equivalent), Kafka (or equivalent), data warehouse (e.g. Hive).
• Industry experience building end-to-end ML/AI infrastructure and/or building and productionizing ML models.
• Exposure to architectural patterns of a large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models).
• Experience with test driven development, familiar with A/B testing, incremental delivery and deployment.

Offices: United States

The Difference You Will Make:

You will architect and implement advanced machine learning solutions—including recommendation engines, ranking systems, intent detection models, and the integration of intelligence into existing platforms. Additionally, you’ll lead efforts to harness the power of Large Language Models (LLMs) to create transformative AI experiences.

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. You will be leading ML, Data and Product engineers to drive ML applications.

A Typical Day:

• Envision, champion, and support the development of novel ML systems, product integrations, and performance optimizations to solve real-world problems
• Lead, mentor, challenge and grow enthusiastic, collaborative software engineers and applied scientists across the organization
• Raise the AI/ML skillset within the organization. A passion for teaching/mentoring is important.

Your Expertise:

• 9+ years of software engineering experience, with 2+ years of experience in Staff Engineer role having ownership responsibility over large-scale software systems
• Background in the design and development of scalable AI and ML systems and services, and a deep passion for building ML-powered products
• You’re an inspiring colleague, a coach and mentor with experience owning and fostering engineering maturity in multiple organizations.
• You’re a builder, and implementer, who seeks out high impact work, and who is: proactive, curious, and an excellent communicator

Offices: United States

The Difference You Will Make:

As a Staff ML Engineer for Payments, you will be the catalyst that transforms bold AI innovation — LLM-powered workflow, real-time fraud defenses, and hyper-personalized 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, latency-first 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, real-time 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:

• 9+ 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.
• Hands-on experience with at least three of the following: PyTorch/TensorFlow , scalable inference stacks (Triton, vLLM), vector search, orchestration/MLOps platforms (Kubeflow, Airflow), large-scale data streaming & processing (Spark, Ray, Kafka).
• Demonstrated success designing, deploying, and monitoring production AI systems—e.g., RAG pipelines, personalization engines, generative content services—complete with drift/cost/latency monitoring, automated re-training 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
  

Offices: United States

The Difference You Will Make:

• As a machine learning engineer or scientist, your expertise will be pivotal in developing AI-powered solutions to shape the future of the Airbnb customer experience with cutting-edge AI techniques. You will drive and guide the rest of the engineers to brainstorm, design and develop AI products and features from inception to production.
• We're seeking a Senior Staff Engineer who thrives at the intersection of technical depth , architectural thinking , and mentorship.
• You’ll collaborate with cross-functional leaders, build resilient systems that operate globally at scale, and help evolve the foundational building blocks behind AI-powered customer support.

While this role won’t own every project below, the below showcase the
breadth and depth of work across our group, and where your leadership may be needed:

• Building a unified, platform-native case management system (AirCase), abstracted via Viaduct APIs and replacing legacy CRM systems.
• Designing scalable AI workflow orchestration to power agent co-pilot tools and intelligent response automation.
• Modernizing our Delivery Management Console (DMC) to include AI powered real-time performance insights, outlier detection, and agent coaching tools.
• Establishing shared data foundations to enable AI/ML solutions, feedback loops, and personalization across the support journey.
• Delivering next generating matching capabilities ( Routing) so incoming customer contacts are matched to the best agents using AI and Intelligence to deliver personalized and differentiated support experiences

A Typical Day:

• Work with large scale structured and unstructured data; explore, experiment, build and continuously improve Machine Learning models and pipelines for Airbnb product, business and operational use cases.
• Work collaboratively with cross-functional partners including product managers, operations and data scientists, to identify opportunities for business impact; understand, refine, and prioritize requirements for machine learning, and drive engineering decisions.
• Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases.
• Leverage third-party and in-house Machine Learning tools & infrastructure to develop reusable, highly differentiating and high-performing Machine Learning systems, enable fast model development, low-latency serving and ease of model quality upkeep.
• Collaborate actively with engineers to apply ML / AI in their solutions to help validate ideas and guide to the right outcomes.
• Partner with other ML Engineers in foundations engineering to mentor and develop initiative to make ML application a core discipline for non ML engineers.

Minimum Qualifications:

• Educational Background : PhD in Computer Science, Mathematics, Statistics, or related technical field.
• Industry Experience : 10+ years of experience in building, testing and shipping AI models and products from inception to production; including 2+ years of experience with GenAI.
• Leadership Experience : 10+ years experience leading and guiding machine learning and AI projects that deliver sizable impact as a senior IC.
• Technical Proficiency : Deep knowledge and hands-on experience with Machine Learning best practices (eg. training/serving skew minimization, feature engineering, feature/model selection), algorithms (eg. neural networks/deep learning, optimization) and domains (eg. NLP, computer vision, personalization, search and recommendation, marketplace optimization, anomaly detection)

Preferred Qualifications:

• Agentic and Automation : Experience with AI technologies in automating processes and developing agentic solutions and frameworks.
• Agile Practice for AI Production : Experience with the entire AI product development lifecycle from incubation to production at scale, following agile practices in the Applied AI/ML domain.

Offices: United States

Solving Identity Defense Problems Including:

• Identity Misuse Detection - Fraudsters increasingly use fake, stolen, or AI-generated identities to gain access to the platform. Traditional verification signals are no longer enough in the face of sophisticated tampering techniques like deepfakes and synthetic imagery. Our team builds advanced detection systems that combine machine learning, computer vision, and biometric signals to identify and stop bad actors in real time. We continuously evolve our models and systems to keep pace with rapidly advancing AI-driven attack vectors, ensuring Airbnb stays one step ahead.
• Duplicate Account Prevention - Airbnb’s integrity depends on enforcing the principle of one account per person. We’re tackling this using identity linking methods that combine graph-based analysis, embeddings, and device IDs. The scale, complexity, and ambiguity of identity data make this one of the most technically demanding problems at Airbnb.
• Underage User Enforcement - Airbnb prohibits users under the age of 18 from accessing the platform, but verifying age accurately—especially across global markets and varying document types—is a nuanced challenge. Fraudsters exploit OCR weaknesses or use borrowed identities to circumvent our policy. We are investing in government ID parsing improvements, tampering detection, and more robust age inference methods to ensure compliance while minimizing false positives. This space also requires deep collaboration with legal and policy teams to ensure regulatory alignment and defensibility across regions.

A Typical Day:

• Train and deploy machine learning models for identity misuse detection and risk scoring.
• Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases.
• Integrate advanced verification methods, including biometrics and NFC-based flows.
• Collaborate closely with ML, iOS/Android, and web engineers to deliver end-to-end solutions.
• Work collaboratively with cross-functional partners including software engineers, product managers, operations and data scientists, identify opportunities for business impact, understand, refine, and prioritize requirements for machine learning models, drive engineering decisions, and quantify impact.
• Contribute to foundational infrastructure including secure data handling, image processing, model serving, and feature engineering.
• Shape technical direction and influence the team roadmap through long-term strategy and investment planning.
• Mentor other engineers and promote best practices to strengthen Airbnb’s engineering culture and foundations.

Your Expertise:

• 9+ years of industry experience in software engineering, with a focus on applied Machine learning.
• BS/MS/PhD in Computer Science, a related field, or equivalent work experience.
• Strong programming (Scala / Python / Java/ C++ or equivalent) skills.
• Deep understanding of Machine Learning best practices (eg. training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (eg. gradient boosted trees, neural networks/deep learning, optimization) and domains (eg. natural language processing, computer vision, personalization and recommendation, anomaly detection).
• Industry experience building end-to-end Machine Learning infrastructure and/or building and productionizing Machine Learning models.
• Strong collaboration skills and experience working with cross-functional teams.
• Comfortable navigating ambiguity and driving projects from concept to production.
• Experience with test driven development, familiar with A/B testing, incremental delivery and deployment.
• Experience with computer vision systems (e.g., face detection, liveness, tampering detection) is a plus.
• Experience with the Trust and Risk domain is a plus.

Offices: United States

The Difference You Will Make:

You will architect and implement advanced machine learning solutions—including recommendation engines, ranking systems, intent detection models, and the integration of intelligence into existing platforms. Additionally, you’ll lead efforts to harness the power of Large Language Models (LLMs) to create transformative AI experiences.

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. You will be leading ML, Data and Product engineers to drive ML applications.

A Typical Day:

• Envision, champion, and support the development of novel ML systems, product integrations, and performance optimizations to solve real-world problems
• Lead, mentor, challenge and grow enthusiastic, collaborative software engineers and applied scientists across the organization
• Raise the AI/ML skillset within the organization. A passion for teaching/mentoring is important.

Your Expertise:

• 12+ years of software engineering experience, with 2+ years of experience in a Principal or Senior Staff Engineer role having ownership responsibility over large-scale software systems
• Background in the design and development of scalable AI and ML systems and services, and a deep passion for building ML-powered products
• You’re an inspiring colleague, a coach and mentor with experience owning and fostering engineering maturity in multiple organizations.
• You’re a builder, and implementer, who seeks out high impact work, and who is: proactive, curious, and an excellent communicator

Offices: United States

The Difference You Will Make:

As a Senior Engineer on our seasoned team, you will be a crucial technical contributor on our most critical initiatives, often engaging with partners well outside of your direct team. You’ll contribute heavily to our flagship initiatives, and you’ll sometimes lead major projects with other engineers and functions, leveraging your skills and experience throughout the full software development lifecycle. Your ingenuity, technical expertise, and leadership abilities will serve as a force multiplier for your team and collaborators. You’ll help level up your team around you in technical and operational excellence, delivering on our short term commitments, while building momentum for the long term.

A Typical Day:

• Design solutions, write code
• Work side by side with your core team, deep in the weeds of the code for services your team owns and operates
• Mentor and inspire your teammates, especially those with less experience than you
• See, own, solve, and execute on your own new ideas that will enable us to build products that can more effectively adapt to the often amorphous world of tax

Your Expertise:

• 5+ years relevant experience as software engineer, with expertise in technologies such as React, TypeScript, GraphQL, Design Systems, etc.
• Able to contribute/operate down the stack as needed: Java, Thrift, Airflow, or similar technologies
• Experience designing, building, launching, and operating complex, user-facing software
• Ability to toggle between executing on company-defined priorities and self-defined goals
• Great at collaborating and influencing technical direction on aspects not directly within your control
• Able to communicate well with a wide variety of cross functional partners such as Legal, Customer Support, Experience Design, etc.
• Skilled at managing initiatives with ambiguous or rapidly shifting requirements
• Able to contribute to the enrichment of the general engineering culture of the wider organization
• Experience with Global Tax or related regulatory/compliance domains highly desirable

Offices: United States