Senior Staff Machine Learning Engineer - AI Safety And Guardrail

Details

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 and experiences that make it possible for guests to connect with communities in a more authentic way.

Community Overview

Machine Learning and Artificial Intelligence are at the heart of the Airbnb product. From Trust to Payments, and from Customer Service to Marketing, Airbnb relies on ML and AI to ensure that guests and hosts have the best possible experience. The Community Support Products (CSP) Machine Learning team drives CSxAI (Community Support x Artificial Intelligence) initiatives by adopting generative AI technologies to enable an intelligent, scalable and exceptional service experience. The team develops and enhances AI models, ML services and tools including LLM fine-tuning and optimization, RAG/Search, LLM evaluation and testing automation, feedback-based learning and guardrails for a wide range of applications in Airbnb.

Role Summary

As a key member of Airbnb’s CSP Machine Learning team, the Guardrail and AI Safety Engineer ensures that AI-powered systems (chatbots, AI assistants, agent copilots) are reliable, safe, and aligned with trust and governance standards. This role collaborates cross-functionally with ML, engineering, product and policy teams to build, monitor, and enforce technical safety mechanisms across the AI system lifecycle.

Responsibilities

• Collaborate with cross-functional teams to identify issues, evaluate risks, design monitoring systems, tailor safeguard measures and deploy solutions to ensure safe, robust and responsible AI adoption in CS products.
• Design and implement guardrails to mitigate risks such as hallucinations, privacy breaches, prompt injections, harmful responses, and bias.
• Set up continuous risk monitoring pipelines and alerting to enable human-in-the-loop feedback and mitigation.
• Work with trust, security, legal and operations teams to enable risk management.
• Collaborate with evaluation and data platform teams to design and build a data flywheel for fixing model failure modes and improving guardrails.
• Partner with product, design, trust & safety, and legal teams to ensure AI-driven features meet global privacy and compliance standards.
• Own documentation, guardrail white papers, and onboarding materials to support knowledge sharing and auditability.
• Partner with ML infrastructure teams to scale safety features across Airbnb products.

Requirements

• PhD or Master’s degree (preferable) in Computer Science or equivalent experience.
• 7+ years (7/10+ stated) of experience developing and deploying machine learning models in production.
• Strong understanding of machine learning principles and algorithms.
• Hands-on programming experience in Python and in-depth knowledge of machine learning frameworks.
• 2+ years of experience in one or more of: Content Safety/Integrity, ML Fairness and Bias, Responsible AI, AI Model Security, or related areas.
• Nice to have: experience with AI technologies in customer support products, LLM alignment techniques (SFT, RLHF, DPO, etc.), and LLM evaluation.

Location & Work Policy

This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed with your manager. Candidates must live in a state where Airbnb, Inc. has a registered entity (some states are excluded). Offices: United States.

Compensation & Benefits

• Base pay range: $244,000 — $305,000 USD (actual base pay depends on experience, skills, business needs, and market demands).
• This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

Inclusion & Accessibility

Airbnb is committed to inclusive hiring and a disability-inclusive application and interview process. Reasonable accommodation requests for recruiting can be sent to [email protected] with full name, role, and accommodation needed.