Senior Staff Machine Learning Engineer, Data & Eval at Airbnb

This is a high-level individual contributor role for an industry veteran who bridges the gap between research and production. The ideal candidate holds a PhD an

Work type: onsite

Location: United States

Salary: $244,000 – $305,000/yr

Type: Full-time

Summary

This is a high-level individual contributor role for an industry veteran who bridges the gap between research and production. The ideal candidate holds a PhD and brings over a decade of experience, specifically focusing on the intersection of Large Language Models (LLMs) and customer experience. You should be an expert in the "CSxAI" domain, capable of leading the technical strategy for Generative AI applications like RAG, agentic workflows, and automated support systems. The compensation is highly competitive, reaching up to $305k base plus equity and travel credits. While listed as "On-site" in the metadata, the description clarifies it is **US-Remote Eligible** in most states, offering significant geographic flexibility. You will join the Core ML team to build the "next generation" of support—transforming how millions of users interact with the platform using state-of-the-art AI. **You might be a good fit if you...** * Have 10+ years of ML experience, including 2+ years specifically in Generative AI. * Hold a PhD in a quantitative field (CS, Math, or Stats). * Have a proven track record of leading applied science teams and shipping models at massive scale. * Are passionate about NLP and building robust evaluation frameworks for AI agents.

Job Description

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.

The Community You Will Join:

AI and ML are at the heart of the Airbnb product. From Trust to Payments, and from Customer Service to Marketing, we rely on ML to ensure that guests and hosts have the best possible experience with Airbnb.

The Core ML team is responsible for driving CSxAI (Customer 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 at Airbnb.

The richness of Airbnb's data, the complexity of its marketplace, and the variety innate in our product mean that we need to operate at the state of the art of AI practice. We are committed to long-term innovation to solve complex problems, and to do that we need experienced ML leaders to join us.

​​The Difference You Will Make:

In this Senior Staff role, you will set technical direction and lead execution for ML evaluation and the end-to-end data flywheel powering CSxAI products (e.g., assistive agents, issue resolution, and tooling). Your work will define how we measure quality, how we turn feedback into learning signals, and how we continuously improve models and products safely and efficiently. You will partner closely with product, engineering, design, operations to build evaluation systems that are trusted, scalable, and actionable - connecting offline metrics to online outcomes.

A Typical Day:

• Work with large scale structured and unstructured data; explore, experiment, build and continuously improve Machine Learning models and pipelines for Airbnb product, business and operational use cases.

• Work collaboratively with cross-functional partners including product managers, operations and data scientists, to identify opportunities for business impact; understand, refine, and prioritize requirements for machine learning, and drive engineering decisions.

• Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases.

• Leverage third-party and in-house Machine Learning tools & infrastructure to develop reusable, highly differentiating and high-performing Machine Learning systems, enable fast model development, low-latency serving and ease of model quality upkeep.

• Define evaluation strategy and success metrics for GenAI systems, aligning offline evaluation with online business and customer experience outcomes.

• Build and scale evaluation frameworks (golden sets, synthetic data, automated regressions, rubric-based grading, LLM-as-judge where appropriate) with strong controls for bias, drift, and reliability.

• Design the data flywheel: instrumentation, feedback collection, data quality checks, labeling strategy, dataset versioning, and governance to support continuous improvement.

• Lead cross-functional quality initiatives across product, ops, and engineering, driving clarity on what “good” looks like and how teams act on evaluation results.

• Develop and productionize pipelines for dataset creation, model monitoring, evaluation-at-scale, and continuous testing (pre-deploy and post-deploy).

• Drive technical decisions and architecture for evaluation and data infrastructure, balancing speed, rigor, cost, and safety.

• Educational Background: PhD in Computer Science, Mathematics, Statistics, or related technical field (or equivalent practical experience).

• Industry Experience: 10+ years building, testing, and shipping ML/AI systems end-to-end; including 2+ years of experience with GenAI/LLM systems in production.

• Leadership Experience: 5+ years leading large, ambiguous technical initiatives as a senior IC, influencing roadmap and engineering/science direction across teams.

• Technical Proficiency:

• Deep expertise in evaluation methodology (offline/online alignment, metric design, human-in-the-loop evaluation, A/B testing, power analysis, regression testing).

• Hands-on experience with GenAI systems, including orchestration, retrieval, tool calling, memory, etc.

• Experience building data pipelines and quality systems (labeling workflows, dataset curation, versioning, monitoring, and governance).

• Solid ML fundamentals and best practices (model selection, training/serving, monitoring, reliability, and model lifecycle management).

• Customer Support Systems: Experience applying ML/AI to customer support workflows (e.g., agent assist, classification/routing, resolution recommendation, QA).

• Infrastructure & Quality at Scale: Experience building robust evaluation platforms for agent behavior validation, safety/guardrails, and continuous improvement.

• Agile Practice for Applied AI: Proven ability to take evaluation and data flywheel work from incubation to production, iterating quickly while maintaining scientific rigor.

• Continuous Learner: Strong curiosity and ability to absorb new techniques (e.g., judge models, preference optimization, synthetic data generation) and apply them pragmatically.

This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity. [Click here](https://careers.airbnb.com/) for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list. If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from.

How We'll Take Care of You:

Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

Pay Range
$244,000—$305,000 USD

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