Senior Machine Learning Engineering

Summary

Join Airbnb's Trust Engineering team and help protect our global community and platform from fraud. You will work with cutting-edge machine learning technologies to build and improve models that detect and prevent fraud, both online and offline. A typical day involves collaborating with operations, data science, and engineering teams to identify and address emerging fraud vectors. You will develop data pipelines, fine-tune models, debug failures, and build automated workflows. This role requires significant experience in applied machine learning and strong programming and data engineering skills. The position is US-remote eligible, with occasional office work or offsites.

Requirements

• 5+ years of industry experience in applied Machine Learning
• Strong programming (Python / Java or equivalent) and data engineering  (SQL / Spark) skills
• Deep understanding of Machine Learning best practices (e.g. training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms and architectures (e.g. gradient boosted trees, neural networks/deep learning, optimization), domains (e.g. natural language processing, computer vision, personalization and recommendation, anomaly detection), and modern tools (LLMs, LVMs)
• Experience with building and fine tuning models using Tensorflow, PyTorch, or Jax
• Industry experience building end-to-end Machine Learning pipelines
• Exposure to architectural patterns of large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models)

Responsibilities

• Work with the operations team to understand new / emerging fraud vectors that are slipping through our defenses
• Write data pipelines to generate labels using an LLM based virtual judge
• Fine tune models to improve accuracy
• Debug failure cases for existing models
• Build LFM based workflows for automation
• Collaborate with cross-functional partners including software engineers, product managers, operations and data scientists to identify opportunities for business impact, and analyze and quantify potential impact

Preferred Qualifications

• An advanced degree such as an MS or  PhD in relevant fields is a plus
• Experience with the Trust and Risk domain is a plus

Benefits

This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits