Airbnb

Senior Machine Learning Engineer, Trust

Airbnb • $150K — $180K *
Consumer Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of industry experience in applied Machine Learning with a solid track record of building and productionizing models.
  • Strong programming skills in Python; familiarity with Scala or Java is a plus.
  • Deep understanding of Machine Learning best practices, including training/serving skew and feature engineering.
  • Proficient with ML frameworks such as TensorFlow or PyTorch.
  • Experience in data engineering and creating end-to-end ML pipelines.
  • Familiarity with the architectural patterns of large-scale software applications.
  • A degree in Computer Science, Machine Learning, or a related field.

Responsibilities

  • Collaborate with cross-functional teams to define and refine ML solutions.
  • Design and productionize end-to-end Machine Learning pipelines for various use cases.
  • Investigate fraud patterns and develop ML-based detection tools.
  • Write, review, and maintain clean, testable code for ML models and pipelines.
  • Work with extensive datasets to enhance ML models for operational purposes.
  • Engage in code reviews and contribute to building a high-quality ML engineering culture.
  • Adapt models and systems in response to evolving fraud threats.

Benefits

  • Remote eligible position allowing flexibility in work location within registered states.
  • Chance to work on impactful projects that enhance user safety and trust.
  • Collaborative environment with talented product managers and engineers.
  • Opportunity to influence the safety and integrity of a global platform.
Full Job Description
The Community You Will Join:

Everyone at Airbnb thinks about trust, but our team obsesses over it daily. At the core of trust is safety, and thus we spend a significant amount of our time and energy keeping the community safe. The Trust team is responsible for developing the technology that helps protect our community and platform from fraud while also ensuring our hosts, guests, homes, and experiences meet our high standards. We constantly work to fight against online fraud (such as monetary loss, compromised accounts, spam and scam in messages, fake inventory, etc.) as well as offline fraud (theft, property damage, personal safety, etc.). We also work on onboarding and screening of users, and think about complex topics like identity and reputation to ensure that every interaction with Airbnb helps build trust in us and our community.

You'll work side-by-side with talented product managers, data scientists, software engineers, fraud intelligence, and operations teams. Together, you'll design and build ML solutions that have direct, meaningful impact on user trust, business success, and the global Airbnb community.

The Difference You Will Make:

As a Senior Machine Learning Engineer on the Trust team, you will actively contribute code and ideas that shape the ML systems protecting millions of Airbnb users. You'll own and deliver ML projects end-to-end - from designing and training models to productionizing and operating them at scale, while collaborating closely with cross-functional partners.

You'll tackle real-world challenges such as account takeover, fake accounts, payment fraud, and bot detection. Your work will help reduce risks posed by bad actors while ensuring the platform remains seamless and welcoming for everyone else. As you develop your skills, you'll see the tangible impact of your models, helping real users stay safe and confident as they travel, host, and connect on Airbnb.

A Typical Day:
  • Collaborate with product managers, data scientists, software engineers, and operations teams to identify opportunities, scope ML solutions, and refine requirements for new or improved Trust models.
  • Design, build, and productionize end-to-end Machine Learning pipelines, including feature engineering, model training, evaluation, and deployment - for both batch and real-time use cases.
  • Investigate emerging fraud patterns and threat signals with your teammates, and develop ML-based detections and tools that enable faster, more accurate responses.
  • Write, review, and ship clean, testable code - whether training a new model, improving an existing pipeline, or optimizing a feature for scalability and reliability.
  • Work with large-scale structured and unstructured data to continuously improve ML models for Airbnb product, business, and operational use cases.
  • Participate in code reviews, design discussions, and cross-team collaborations to contribute to a high-quality ML engineering culture.
  • Work closely with trust defense and platform teams to adapt models and systems to an evolving landscape of fraud attacks.

Your Expertise:
  • 5+ years of industry experience in applied Machine Learning, with a track record of building and productionizing models at scale.
  • Strong programming skills in Python (required) and familiarity with Scala, Java, or equivalent.
  • Solid understanding of Machine Learning best practices - e.g., training/serving skew minimization, A/B testing, feature engineering, model selection - and algorithms such as gradient boosted trees, neural networks, transformers, and deep learning.
  • Experience with ML frameworks and tooling such as TensorFlow, PyTorch, or equivalent.
  • Experience with data engineering and building end-to-end ML pipelines, including both batch and real-time systems.
  • Exposure to architectural patterns of large, high-scale software applications (e.g., well-designed APIs, high-volume data pipelines, efficient algorithms).
  • Experience with test-driven development, incremental delivery, and deployment practices.
  • Exposure to the Trust and Risk domain (e.g., fraud detection, anomaly detection, identity, account integrity) is a plus.
  • A Bachelor's, Master's, or PhD in CS/ML or a related field.

Your Location:

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 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.

About Airbnb

Airbnb is an online community marketplace for people to list, discover, and book accommodations through mobile phones or the Internet. The company connects travelers seeking authentic experiences with hosts offering unique, inspiring spaces. Whether the available space is a castle for a night, a sailboat for a week, or an apartment for a month, Airbnb is the easiest way for people to showcase these distinctive spaces to an audience of millions. By facilitating bookings and financial transactions, Airbnb makes the process of listing or booking a space effortless and efficient. With 4,500,000 listings in over 65,000 cities in 191 countries, the company offers the widest variety of unique spaces for everyone at any price point around the globe.

Airbnb Careers

Join the vibrant team at Airbnb, the world’s leading community-driven hospitality company, where innovation, leadership, and diversity training are at the heart of our professional ethos. At Airbnb, we offer more than just job opportunities; we provide a platform for growth, learning, and meaningful connections. Work You’ll Do Become a part of Airbnb’s dynamic team and contribute to reshaping the travel and hospitality landscape globally. Our commitment to innovation and cultural understanding sets us apart, allowing us to enhance the travel experience for millions of users worldwide. Lead with Innovation and Diversity At Airbnb, we believe in leading with innovation and embracing diversity. Our leadership is committed to fostering an inclusive environment where every team member can thrive. Diversity training is integral to our operations, ensuring that we continue to be a leader in creating inclusive travel experiences. Explore Professional Growth and Development Airbnb offers a wealth of career advancement opportunities, supported by robust training programs and professional development courses. Whether you’re looking for a full-time position or an internship, Airbnb empowers you to excel and grow your career to new heights. Join Our Global Team Work alongside a global team of passionate, creative, and solution-driven professionals. At Airbnb, we value the skills and perspectives of our diverse team members, and we continuously strive to leverage this collective power to innovate and lead in the industry. Benefits and Culture Airbnb is dedicated to providing its employees with a supportive and empowering work environment. Our benefits package is designed to enhance your life both inside and outside of work. Enjoy comprehensive health benefits, flexible working conditions, and unique perks that encourage a balance of work and life. Networking and Career Opportunities Expand your professional network within Airbnb through various networking events, mentorship programs, and collaborative projects. Our vibrant culture of connectivity opens doors to enriching career paths and professional relationships. Apply Now Ready to take the next step in your career? Explore the exciting job opportunities and internships available at Airbnb. We are actively hiring talented individuals who are passionate about making a difference in the world of travel. Visit our Careers Page Stay updated with the latest from Airbnb Careers by visiting our dedicated careers page. Discover new job openings, read about our company culture, and find tips for your resume and interview preparation. Join Airbnb and be part of a team that’s committed to redefining the future of travel through innovation, leadership, and a deep respect for diverse cultures and communities. Your journey to a fulfilling career starts here.
Learn more about Airbnb
Size
5,000 employees
Market Cap
$52.6 billion
Industry
Net Income
-$4.5 billion
Founded
2008
5 Year Trend
+29.3%
Revenue
$3.3 billion
NASDAQ

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