3 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 operates a global online marketplace that connects hosts offering homes, rooms, and unique properties with travelers seeking short-term stays and experiences. The company earns revenue primarily through service fees on bookings; founded in 2007 and headquartered in San Francisco, it is a public company on NASDAQ (ABNB) with over 5 million hosts and guest arrivals recorded in nearly every country.