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# Machine Learning Engineer, Relevance and Personalization (Query Intelligence)

- **Company:** Airbnb
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $200,000.0 - $235,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Software Applications, Architectural Patterns, EXEC (Scripting Language), Encodings, Cyber Security, Data Pipelines, Servicenow
- **Published:** July 15, 2026
- **Apply:** https://www.builtincolorado.com/auth/login?destination=/job/senior-machine-learning-engineer-relevance-and-personalization-query-intelligence/10195110

## About the Role

* 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 (eg. training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (eg. neural networks/deep learning, optimization) and domains (eg. 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).

## Description

Lead end-to-end execution of packaging category sourcing across assigned markets: manage supplier relationships, run RFP/RFI and contract negotiations, ensure supply continuity and risk mitigation, drive supplier performance and cost optimization, and collaborate with cross-functional teams to deliver category outcomes for the QSR system.


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