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Senior Staff Machine Learning Engineer, Trust

Airbnb· Trust Engineering
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Hybrid (USA), United States$244k - $305kfull-timePosted 6mo ago

About the role

Senior technical individual contributor in Airbnb's Trust Engineering, focusing on advancing production ML systems to protect the community from fraud and build trust across the platform. Hands-on leader responsible for designing long-term ML strategy, mentoring engineers, and delivering large-scale ML initiatives.

Responsibilities

  • 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.
  • Serve as a technical leader and mentor to other ML and software engineers, providing guidance on architectural and modeling challenges and raising the technical bar.
  • Drive and deliver large-scale, multi-quarter ML initiatives spanning multiple teams, influencing roadmaps and ensuring alignment between platform and product
  • Work with large scale structured and unstructured data, build and continuously improve cutting edge ML models for Airbnb product, business and operational use cases.
  • Collaborate with cross-functional partners (software engineers, product managers, operations, data scientists) to identify opportunities for business impact, refine requirements, drive engineering decisions, and quantify impact.
  • Work closely with trust defense and platform teams to tackle evolving fraud threats.
  • Hands-on development, productionization, and operation of ML models and pipelines at scale (batch and real-time).
  • Examples include: Anomaly detection models, ML models for continuous risk evaluation, Multimodality and Agentic AI.

Qualifications

  • 12+ years of industry experience in applied Machine Learning
  • 2-3+ years working with LLMs and novel GenAI technologies; proficiency with Agentic AI (frameworks, orchestration, architecture, productionization)
  • A Bachelor’s, Master’s or PhD in CS/ML or related field
  • Strong programming skills (Scala / Python / Java / C++ or equivalent) and data engineering
  • Deep understanding of ML best practices and algorithms (e.g., training/serving skew minimization, A/B testing, feature engineering, feature/model selection; gradient boosted trees; neural networks; optimization) and domains (genAI, Agentic AI, NLP, CV, personalization/recommendation, anomaly detection)
  • Experience with AgenticAI, TensorFlow, PyTorch, Kubernetes
  • Industry experience building end-to-end ML and Agentic infrastructure and/or productionizing models
  • Exposure to architectural patterns of large-scale software (APIs, high-volume data pipelines, efficient algorithms)
  • Experience with test-driven development, A/B testing, incremental delivery and deployment
  • Experience in Trust and Risk domain is a plus

Skills

Required:ML system design and strategyLeadership and mentorshipLarge-scale ML implementationGenAI / LLMs / Agentic AIProgramming

Benefits

  • Not specified in this description
Last updated Oct 22, 2026. Interested? Apply on the company site.
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About Airbnb

Book accommodations around the world.

Founded in August of 2008 and based in San Francisco, California, Airbnb is a trusted community marketplace for people to list, discover, and book unique accommodations around the world — online or from a mobile phone. Whether an apartment for a night, a castle for a week, or a villa for a month, Airbnb connects people to unique travel experiences, at any price point, in more than 33,000 cities and 192 countries. And with world-class customer service and a growing community of users, Airbnb is the easiest way for people to monetize their extra space and showcase it to an audience of millions. No global movement springs from individuals. It takes an entire team united behind something big. Together, we work hard, we laugh a lot, we brainstorm nonstop, we use hundreds of Post-Its a week, and we give the best high-fives in town. Headquartered in San Francisco, we have satellite offices in Dublin, London, Barcelona, Paris, Milan, Copenhagen, Berlin, Moscow, São Paolo, Sydney, and Singapore.

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