Senior Machine Learning Engineer, Trust

Details

Airbnb's Trust Frontier AI team develops specialized models, AI agents, and evaluation systems for mission-critical trust and safety problems, including fraud prevention, abuse detection, identity, and account integrity. The team prototypes and productionizes AI solutions that protect Airbnb users and measures their impact on business and operational metrics.

Responsibilities

• Frame and prototype machine learning and agentic solutions for ambiguous trust and safety problems in partnership with product managers, data scientists, and frontline defense teams.
• Design, build, and productionize end-to-end machine learning pipelines, including feature engineering, model training, evaluation, and deployment for batch and real-time use cases.
• Build and improve abuse behavior detection systems that generalize across defenses.
• Design, launch, and iterate on AI agents that automate trust decisions, including orchestration, tool interfaces, and quality guardrails.
• Build benchmarks, evaluation harnesses, and instrumentation to objectively measure agentic and model decision quality.
• Develop specialized trust and safety models and use LLMs and AI agents to accelerate model development.
• Write, review, and ship clean, testable code for model training, pipeline improvements, and scalable, reliable features.
• Work with large-scale structured and unstructured data to continuously improve machine learning models for product, business, and operational use cases.
• Partner with frontline defense teams to validate solutions through experiments and holdouts and quantify their impact on business and operational metrics.
• Participate in code reviews, design discussions, and cross-team collaboration.

Requirements

• 5–10 years of industry experience in applied machine learning, with a track record of building and productionizing models at scale.
• 1–2 or more years of hands-on experience with LLMs and generative AI technologies, including agentic frameworks, orchestration, and evaluation.
• Strong Python programming skills; familiarity with Scala, Java, or equivalent.
• Strong understanding of machine learning best practices, including training-serving skew minimization, A/B testing, feature engineering, and model selection.
• Knowledge of gradient-boosted trees, neural networks, transformers, and deep learning.
• Experience with machine learning frameworks and tooling such as TensorFlow or PyTorch.
• Experience with data engineering and end-to-end machine learning pipelines, including batch and real-time systems.
• Experience designing evaluation methodologies for machine learning or LLM systems, including benchmarks, ground truth, offline and online metrics, and calibration.
• Ability to work with ambiguity, scope loosely defined problems, prototype quickly, and drive solutions to measurable outcomes.
• Exposure to architectural patterns for large-scale software applications, including well-designed APIs, high-volume data pipelines, and efficient algorithms.
• Experience with test-driven development, incremental delivery, and deployment practices.
• Experience with multimodal models such as vision, document, or speech models is a plus.
• Exposure to trust and risk domains such as fraud detection, anomaly detection, identity, or account integrity is a plus.
• Bachelor's, Master's, or PhD in computer science, machine learning, or a related field.

Location

This position is US remote eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed with the manager. Candidates must live in a state where Airbnb, Inc. has a registered entity.

Benefits

The role may be eligible for bonus, equity, benefits, and Employee Travel Credits.

Compensation

The base pay range is $200,000–$235,000 USD.