Senior Machine Learning Engineer, Trust

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop and prototype machine learning and autonomous solutions for challenges lacking established methodologies

• Create, construct, and implement comprehensive machine learning pipelines for both batch and real-time applications

• Enhance and refine abuse behavior detection across various defense mechanisms

• Conceive, launch, and iterate on AI agents responsible for automating trust-related decisions

• Establish benchmarks, evaluation tools, and instrumentation to assess the quality of model and agent decisions

• Create specialized trust and safety models utilizing large language models and AI agents

• Write, review, and deliver clean, testable code

• Work with extensive structured and unstructured datasets to enhance machine learning models

• Collaborate with frontline defense teams to validate solutions through experiments and holdout tests

• Engage in code reviews, design discussions, and cross-team collaborations

⛳️ Requirements

• 5–10 years of professional experience in applied machine learning, focusing on building and deploying models at scale

• 1–2+ years of practical experience with large language models and generative AI technologies, including agentic frameworks, orchestration, and evaluation

• Proficient programming skills in Python (required)

• Familiarity with Scala, Java, or similar languages

• Knowledge of machine learning best practices, such as minimizing training/serving skew, A/B testing, feature engineering, and model selection

• Understanding of gradient boosted trees, neural networks, transformers, and deep learning techniques

• Proficient in TensorFlow, PyTorch, or equivalent frameworks

• Experience in data engineering and end-to-end machine learning pipelines for both batch and real-time systems

• Proven experience in designing evaluation methodologies for machine learning or LLM systems, including benchmarks, ground truth, offline/online metrics, and calibration

• Familiarity with architectural patterns of large-scale software applications

• Experience with test-driven development, incremental delivery, and deployment practices

• Experience with multimodal models is advantageous

• Exposure to the Trust and Risk domain is a plus

• Bachelor's, Master's, or PhD in Computer Science, Machine Learning, or a related field

🏝️ Benefits

• Eligible for bonus

• Eligible for equity

• Comprehensive benefits package

• Employee Travel Credits

• Opportunities for occasional offsite attendance

• Possibility of working at an Airbnb office occasionally, as coordinated with the manager

• Disability-inclusive application and interview accommodations