Senior Staff Machine Learning Engineer, Growth Platform Engineering

Details

Airbnb's Growth Platform team builds AI-powered systems and capabilities to support the growth of Airbnb products. The platform delivers personalized content and product experiences across Airbnb and digital marketing channels, including landing pages, email, push notifications, SMS, and digital advertising. The team is progressing from AI-assisted to agentic and autonomous systems with human-in-the-loop controls for brand safety, quality, and compliance.

Responsibilities

• Develop AI-powered solutions for Airbnb's agentic growth platform using advanced AI and machine learning techniques.
• Guide engineers in brainstorming, designing, and developing AI products and features from inception through production.
• Build resilient systems that operate globally at scale and evolve foundational components for AI-powered growth systems.
• Develop agentic capabilities for personalized content generation, including emails, push notifications, advertising copy, and creatives.
• Build ML and AI orchestration systems to determine optimal audiences, messages, channels, and communication timing.
• Design proactive marketing analyst agents that identify marketing opportunities and convert them into executable campaigns.
• Work with large-scale structured and unstructured data to explore, experiment with, build, and improve machine learning models and pipelines.
• Collaborate with product managers, operations teams, and data scientists to identify business opportunities, refine machine learning requirements, and drive engineering decisions.
• Develop, productionize, and operate ML and AI models and pipelines at scale for batch and real-time use cases.
• Use third-party and in-house machine learning tools and infrastructure to enable reusable, high-performing systems, fast model development, low-latency serving, and model quality maintenance.
• Collaborate with engineers to apply ML and AI to their solutions, validate ideas, and guide outcomes.
• Mentor ML and AI engineers and help make ML and AI applications a core discipline for non-ML and non-AI engineers.

Requirements

• 12+ years of industry experience in applied ML and AI, inclusive of an MS or PhD in a relevant field.
• Strong programming and data engineering skills in Scala, Python, Java, C++, or equivalent technologies.
• Deep understanding of machine learning and AI best practices, including training-serving skew minimization, A/B testing, feature engineering, and feature and model selection.
• Strong knowledge of algorithms including gradient-boosted trees, neural networks, deep learning, and optimization.
• Experience in domains such as natural language processing, computer vision, personalization, search and recommendation, marketplace optimization, and anomaly detection.
• Experience with TensorFlow, PyTorch, Kubernetes, Airflow or equivalent, and Kafka or equivalent.
• Expertise in architectural patterns for large-scale software applications, including well-designed APIs, high-volume data pipelines, efficient algorithms, and models.

Preferred Qualifications

• Experience using AI technologies to automate processes and develop agentic solutions and frameworks.
• Experience across the complete AI product development lifecycle, from incubation through production at scale, using agile practices in applied AI and ML.
• Experience building robust testing frameworks for agent behavior validation and continuous improvement.
• Experience driving architectural requirements for machine learning infrastructure.

Work Location

This is a US remote-eligible position. Occasional work at an Airbnb office or attendance at offsites may be required as agreed with the manager. Candidates must live in a state where Airbnb, Inc. has a registered entity and must meet the applicable state eligibility requirements.

Benefits

The role may be eligible for bonus, equity, benefits, and Employee Travel Credits. Airbnb states that base pay depends on factors including training, transferable skills, work experience, business needs, and market demands.