2 months ago
Base Salary
$244k - $305k/yr
Responsibilities
- Define and execute the long-term ML technical vision and strategy for Trust, including scalable architecture and engineering best practices.
- Lead and deliver large-scale, multi-quarter ML initiatives across multiple teams while influencing roadmaps and aligning platform and product efforts.
- Develop, productionize, and operate machine learning models and pipelines at scale for batch and real-time use cases.
- Build and improve ML models using large-scale structured and unstructured data for product, business, operational, fraud, and risk use cases.
- Provide technical leadership and mentorship to ML and software engineers on architectural and modeling challenges.
- Collaborate with software engineers, product managers, operations, and data scientists to prioritize requirements, make engineering decisions, and quantify impact.
- Work with trust defense and platform teams to address changing fraud attacks.
- Contribute hands-on code as a senior individual contributor.
Requirements
- 12+ years of industry experience in applied machine learning.
- 2–3+ years of experience working with LLMs and novel GenAI technologies, including proven experience with agentic AI frameworks, orchestration, architecture, and productionization.
- Bachelor’s, Master’s, or PhD in computer science, machine learning, or a related field.
- Strong programming skills in Scala, Python, Java, C++, or equivalent, along with data engineering skills.
- Deep understanding of ML best practices, including training/serving skew minimization, A/B testing, feature engineering, feature selection, and model selection.
- Knowledge of ML algorithms and domains including gradient-boosted trees, neural networks/deep learning, optimization, GenAI, agentic AI, natural language processing, computer vision, personalization and recommendation, and anomaly detection.
- Experience with AgenticAI, TensorFlow, PyTorch, and Kubernetes.
- Experience building end-to-end machine learning and agentic infrastructure and/or building and productionizing ML models.
- Experience with architectural patterns for large-scale software applications, high-volume data pipelines, APIs, efficient algorithms, and models.
- Experience with test-driven development, A/B testing, incremental delivery, and deployment.
- Experience in the Trust and Risk domain is a plus.
Benefits
- US remote eligible, with possible occasional work at an Airbnb office or attendance at offsites as agreed with the manager.
- May be eligible for bonus, equity, benefits, and Employee Travel Credits.
- Airbnb provides disability-inclusive application and interview accommodations.
Tech Stack
Categories
About Airbnb
Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays, experiences and services that make it possible for guests to connect with communities in a more authentic way.