Senior Staff Machine Learning Engineer, Trust

Airbnb Airbnb · Consumer · United States · Software Engineering

Senior Staff Machine Learning Engineer on the Trust team at Airbnb, focusing on developing and productionizing ML models and pipelines, including LLMs and Agentic AI, for fraud detection and platform safety. This role requires hands-on coding and technical leadership in a large-scale, regulated environment.

What you'd actually do

  1. Define and execute on the long-term ML technical vision and strategy for the Trust organization, identifying key investments, architecting scalable solutions, and championing best practices that advance the state-of-the-art in production ML systems.
  2. Serve as a technical leader and mentor to other ML and software engineers across the organization, providing guidance on complex architectural and modeling challenges, and raising the overall technical bar.
  3. Drive and deliver large-scale, multi-quarter ML initiatives that span multiple teams, influencing roadmaps and ensuring alignment between platform and product
  4. Work with large scale structured and unstructured data, build and continuously improve cutting edge Machine Learning models for Airbnb product, business and operational use cases.
  5. Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases.

Skills

Required

  • Applied Machine Learning
  • LLMs
  • GenAI technologies
  • Agentic AI
  • Frameworks
  • Orchestration
  • Architecture
  • Productionization
  • Scala
  • Python
  • Java
  • C++
  • Data engineering
  • Machine Learning best practices
  • Gradient boosted trees
  • Neural networks
  • Deep learning
  • Optimization
  • Natural language processing
  • Computer vision
  • Personalization
  • Recommendation systems
  • Anomaly detection
  • AgenticAI
  • Tensorflow
  • PyTorch
  • Kubernetes
  • Machine Learning infrastructure
  • Agentic infrastructure
  • Large-scale software applications
  • Well-designed APIs
  • High volume data pipelines
  • Efficient algorithms
  • Test driven development
  • A/B testing
  • Incremental delivery
  • Deployment

Nice to have

  • Trust and Risk domain

What the JD emphasized

  • 12+ years of industry experience in applied Machine Learning
  • 2-3+ years working with LLMs and novel GenAI technologies
  • Proficiency and proven experience on Agentic AI (frameworks, orchestration, architecture and productionization)
  • Strong programming (Scala / Python / Java/ C++ or equivalent) and data engineering skills
  • Deep understanding of Machine Learning best practices
  • Industry experience building end-to-end Machine Learning and Agentic infrastructure and/or building and productionizing Machine Learning models

Other signals

  • Develop and productionize ML models and pipelines
  • Agentic AI
  • LLMs and GenAI technologies
  • Trust and Risk domain