Senior Machine Learning Engineer, Relevance

Airbnb

14h•$200,000 - $235,000•Remote

About The Position

The Senior Machine Learning Engineer will join Airbnb’s Relevance and Personalization team, which develops search and recommendation systems across Airbnb’s digital platform. The role focuses on end-to-end ranking algorithms and ecosystems that optimize multiple business objectives, using structured and unstructured data and supporting a healthy marketplace for hosts and guests. The engineer will build and improve machine learning models for product, business, and operational use cases; develop and operate models and data pipelines at scale for batch and real-time use; and use machine learning tools and infrastructure to create reusable, high-performing systems that support rapid model development, low-latency serving, and model quality upkeep. The role collaborates with software engineers, product managers, operations teams, and data scientists to identify opportunities, prioritize requirements, make engineering decisions, and measure impact. Example projects include feature platforms, model interpretability, hyperparameter optimization, and concept drift detection. This position is US-remote eligible, with occasional work at an Airbnb office or attendance at offsites as agreed with the manager. Employees must live in a state where Airbnb, Inc. has a registered entity. The position may be eligible for a bonus, equity, benefits, and Employee Travel Credits.

Requirements

At least 5 years of industry experience in applied machine learning, inclusive of an MS or PhD in a relevant field.
Strong programming and data engineering skills, using Scala, Python, Java, C++, or equivalent.
Deep understanding of machine learning best practices, including minimizing training/serving skew, A/B testing, feature engineering, and feature/model selection.
Understanding of machine learning algorithms such as neural networks, deep learning, and optimization, and domains such as NLP, computer vision, personalization, search and recommendation, marketplace optimization, or anomaly detection.
Experience with at least three of the following technologies or equivalents: TensorFlow, PyTorch, Kubernetes, Spark, Airflow, Kafka, 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 used in large-scale software applications, such as 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.

Responsibilities

Build and continuously improve machine learning models for Airbnb product, business, and operational use cases using large-scale structured and unstructured data.
Collaborate with software engineers, product managers, operations, and data scientists to identify opportunities for business impact, refine and prioritize model requirements, drive engineering decisions, and quantify impact.
Develop, productionize, and operate machine learning models and pipelines at scale, including batch and real-time use cases.
Use third-party and in-house machine learning tools and infrastructure to build reusable, high-performing systems that enable fast model development, low-latency serving, and model quality upkeep.
Contribute to end-to-end search ranking systems and ecosystems that optimize multiple business objectives.