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From the employer's careers site First seen 18 Apr 2026 · Still live on 13 Nov 2026

Senior Staff Machine Learning Engineer, Data & Eval

Airbnb United States Remote staff full-time

Salary

$244,000-$305,000 USD

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Description

We're looking for a Senior Staff Machine Learning Engineer to join our Core ML team. As a key member of our team, you will be responsible for driving CSxAI (Customer Support x Artificial Intelligence) initiatives by adopting Generative AI technologies to enable an intelligent, scalable, and exceptional service experience.

In this role, you will set technical direction and lead execution for ML evaluation and the end-to-end data flywheel powering CSxAI products. 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, and operations to build evaluation systems that are trusted, scalable, and actionable - connecting offline metrics to online outcomes.

A typical day in this role will involve working with large-scale structured and unstructured data, exploring, experimenting, building, and continuously improving Machine Learning models and pipelines for Airbnb product, business, and operational use cases.

You will 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 development, productionization, and operation of Machine Learning models and pipelines at scale, including both batch and real-time use cases, will also be a key part of this role.

You will leverage third-party and in-house Machine Learning tools and 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.

Your expertise will be critical in defining evaluation strategy and success metrics for GenAI systems, aligning offline evaluation with online business and customer experience outcomes.

You will build and scale evaluation frameworks with strong controls for bias, drift, and reliability, design the data flywheel, and lead cross-functional quality initiatives across product, ops, and engineering.

You will develop and productionize pipelines for dataset creation, model monitoring, evaluation-at-scale, and continuous testing, and drive technical decisions and architecture for evaluation and data infrastructure.

Minimum qualifications for this role include a PhD in Computer Science, Mathematics, Statistics, or a related technical field, industry experience of 10+ years building, testing, and shipping ML/AI systems end-to-end, and leadership experience of 5+ years leading large, ambiguous technical initiatives as a senior IC.

Preferred qualifications include customer support systems experience, infrastructure and quality at scale experience, agile practice for applied AI experience, and continuous learner experience.

This position is US-Remote Eligible, and the role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager.

Our job titles may span more than one career level, and 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 $244,000-$305,000 USD, and this role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

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Skills

Required

  • evaluation methodology
  • GenAI systems
  • data pipelines
  • quality systems
  • ML fundamentals
  • best practices

Nice to have

  • customer support systems
  • infrastructure and quality at scale
  • agile practice for applied AI
  • continuous learner

Ready to apply?

You apply with the employer directly. Their original posting is here: https://job-boards.greenhouse.io/airbnb/jobs/6757302

Apply on Airbnb