Machine Learning Engineer, Relevance and Personalization

This is a fully remote position, open to applicants in United States.

📋 Description

• Collaborate with large-scale structured and unstructured datasets to develop and continuously enhance innovative Machine Learning models for various Airbnb product, business, and operational applications.

• Partner effectively with cross-functional teams, including software engineers, product managers, operations, and data scientists, to identify business impact opportunities, refine and prioritize machine learning model requirements, drive engineering decisions, and measure impact.

• Engage in hands-on development, production, and operation of Machine Learning models and pipelines at scale, covering both batch and real-time scenarios.

• Utilize both third-party and in-house Machine Learning tools and infrastructure to create reusable, highly distinctive, and high-performance Machine Learning systems that support rapid model development, low-latency serving, and efficient model quality maintenance.

⛳️ Requirements

• Recent Ph.D. graduate in ML/AI or a minimum of 2 years of industry experience in applied ML/AI with an M.S. or B.S. degree.

• Proficient programming skills in Scala, Python, Java, C++, or similar languages, along with strong data engineering capabilities.

• In-depth knowledge of Machine Learning best practices (such as minimizing training/serving skew, A/B testing, feature engineering, and feature/model selection), algorithms (including neural networks/deep learning and optimization), and domains (e.g., natural language processing, computer vision, personalization, search and recommendation, marketplace optimization, anomaly detection).

• Familiarity with at least three of the following technologies: Tensorflow, PyTorch, Kubernetes, Spark, Airflow (or their equivalents), Kafka (or equivalents), and data warehouses (e.g., Hive).

• Understanding of architectural patterns in large, high-scale software applications (such as well-designed APIs, high-volume data pipelines, efficient algorithms, and models).

• Demonstrated ability to select the appropriate ML method to address challenges within current constraints while maintaining a clear vision for future iterations and balancing exploration and exploitation of various techniques.

• Capacity to delve deeply into building the most impactful solutions while simultaneously guiding multiple initiatives across various teams and organizations to ensure the success of our mission.

🏝️ Benefits

• This position may also be eligible for bonuses, equity, benefits, and Employee Travel Credits.