Senior Machine Learning Engineer, Relevance and Personalization

Details

The Relevance and Personalization team at Airbnb develops search and recommendation systems across the company’s digital platform. This role focuses on building end-to-end ranking algorithms and machine learning ecosystems that optimize multiple business objectives.

The team works across the end-to-end search ranking product stack, including data pipelines, feature and model innovation, serving, and experimentation. Systems leverage structured, sequential, image, and text data to support ranking solutions for Airbnb’s hosts and guests.

Responsibilities

• Work with large-scale structured and unstructured data to build and continuously improve machine learning models for product, business, and operational use cases.
• Collaborate with software engineers, product managers, operations, and data scientists to identify opportunities for business impact, refine and prioritize machine learning requirements, drive engineering decisions, and quantify impact.
• Develop, productionize, and operate machine learning models and pipelines at scale for batch and real-time use cases.
• Leverage third-party and in-house machine learning tools and infrastructure to build reusable, high-performing machine learning systems.
• Enable fast model development, low-latency serving, and efficient model quality maintenance.
• Contribute to projects such as feature platforms, model interpretability, hyperparameter optimization, and concept drift detection.

Requirements

• 5+ years of industry experience in applied machine learning, including experience associated with an MS or PhD in a relevant field.
• Strong programming and data engineering skills using Scala, Python, Java, C++, or equivalent technologies.
• Deep understanding of machine learning best practices, including training-serving skew minimization, A/B testing, feature engineering, and feature and model selection.
• Knowledge of machine learning algorithms, including neural networks, deep learning, and optimization.
• Experience in relevant domains such as natural language processing, computer vision, personalization, search and recommendation, or marketplace optimization.
• Experience with at least three of the following technologies: TensorFlow, PyTorch, Kubernetes, Spark, Airflow or equivalent, Kafka or equivalent, and data warehouses such as Hive.
• Industry experience building end-to-end machine learning infrastructure and/or building and productionizing machine learning models.
• Exposure to architectural patterns for large-scale software applications, including well-designed APIs, high-volume data pipelines, efficient algorithms, and models.
• Experience with test-driven development and familiarity with A/B testing, incremental delivery, and deployment.
• Experience applying large language models and modern NLP, such as sequence tagging, text generation, intent classification, or representation learning, is a plus.
• Familiarity with natural-language, AI-native search experiences, such as autocomplete or smart compose, query understanding, or user-intent modeling, is a plus.

Location

This position is US remote eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed with the manager. The employee must live in a state where Airbnb, Inc. has a registered entity.

Benefits

The role may be eligible for bonus, equity, benefits, and Employee Travel Credits. Airbnb is committed to an inclusive application and interview process and provides reasonable accommodations for candidates with disabilities.

Compensation

The base pay range is $191,000–$225,000 USD per year. Actual base pay depends on factors including training, transferable skills, work experience, business needs, and market demands.