Senior Staff Machine Learning Engineer, Infrastructure

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:  At Airbnb, our mission is to create a world where anyone can belong anywhere. We use advanced Data and Machine Learning extensively to create a more connected, empowered, and safer global community, and to enable an intelligent & worry-free travel experience. ML Infrastructure, which is the team you will join in, is tasked to provide robust, scalable, and innovative common shared foundations for modeling, data, governance and productivity, to ensure Airbnb’s AI/ML models and applications are built with the highest standards in the industry. The Difference You Will Make: As part of our team, you'll play a pivotal role in shaping our cutting-edge Generative AI infrastructure, positioning AI at the heart of Airbnb’s future. You'll build the essential AI/ML data foundations to power diverse AI/ML use cases across Airbnb. You’ll define, implement and champion industry-leading best practices to streamline data asset creation, management and utilization, ensuring efficiency, consistency, and regulatory compliance. Your contributions will significantly accelerate AI/ML innovation, facilitating rapid development and deployment of high-quality, highly impactful AI/ML solutions throughout the company. 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. Experience building end-to-end AI/ML platforms and deploying production-grade AI/ML models. Familiarity with state-of-the-art LFMs such as Llama, Mixtral, CLIP, and the Qwen series. Hands-on experience developing RAG platform, leaderboards, chatbots, and agentic AI applications. Expertise in AI/ML governance, compliance, and regulatory frameworks. 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