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Senior Machine Learning Engineer, Query Intelligence

Airbnb· Relevance and Personalization
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Hybrid (United States)$200k - $235kFull-timePosted 3mo ago

About the role

Senior ML Engineer focusing on query intelligence within Airbnb’s Relevance and Personalization team, building end-to-end ML systems for search, autocomplete, tagging, expansion, and intent modeling across Stays, Experiences, and Services.

Responsibilities

  • Work with large scale structured and unstructured data, build and continuously improve cutting edge Machine Learning models for Airbnb product, business and operational use cases, with a focus on query understanding.
  • Develop query understanding capabilities — autocomplete and smart compose, query tagging (sequence tagging / NER), query expansion, and query/user intent modeling — and natural-language search experiences powered by modern NLP and LLMs.
  • 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 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.
  • Example projects include: smart compose and language generation for search, LLM-based sequence taggers, LLM-driven query/location expansion, intent classification, and user-intent sequence modeling.

Qualifications

  • 5+ years of industry experience in applied Machine Learning, inclusive MS or PhD in relevant fields.
  • Strong programming (Scala / Python / Java / C++ or equivalent) and data engineering skills.
  • Deep understanding of Machine Learning best practices (training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (neural networks/deep learning, optimization) and domains (natural language processing, personalization, search and recommendation, marketplace optimization).
  • Experience with 3 or more of these technologies: Tensorflow, PyTorch, Kubernetes, Spark, Airflow (or equivalent), Kafka (or equivalent), data warehouse (eg. Hive).
  • Industry experience building end-to-end Machine Learning models.
  • Experience applying large language models and modern NLP — e.g., sequence tagging/NER, text generation, intent classification, or embedding/representation learning.
  • Familiarity with building natural-language, AI-native and agentic search experiences is a plus.
  • Exposure to architectural patterns of large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models).

Skills

Required:Query understanding

Benefits

  • Note: Benefits are described generally in the job description as part of Airbnb’s inclusion and equal opportunity commitments and may vary by location.
Last updated Oct 22, 2026. Interested? Apply on the company site.
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About Airbnb

Book accommodations around the world.

Founded in August of 2008 and based in San Francisco, California, Airbnb is a trusted community marketplace for people to list, discover, and book unique accommodations around the world — online or from a mobile phone. Whether an apartment for a night, a castle for a week, or a villa for a month, Airbnb connects people to unique travel experiences, at any price point, in more than 33,000 cities and 192 countries. And with world-class customer service and a growing community of users, Airbnb is the easiest way for people to monetize their extra space and showcase it to an audience of millions. No global movement springs from individuals. It takes an entire team united behind something big. Together, we work hard, we laugh a lot, we brainstorm nonstop, we use hundreds of Post-Its a week, and we give the best high-fives in town. Headquartered in San Francisco, we have satellite offices in Dublin, London, Barcelona, Paris, Milan, Copenhagen, Berlin, Moscow, São Paolo, Sydney, and Singapore.

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