Senior Staff Machine Learning Engineer, Trust

Traveltechessentialist; United States; Remote; USD 180,000 - 260,000; Full time

Benefits offered by this job

Bonus opportunities

Equity options

Employee Travel Credits

Job summary

A leading hospitality company is looking for a Senior Machine Learning Engineer to enhance trust and safety measures on their platform. This role includes driving long-term ML strategies, mentoring other engineers, and delivering complex ML initiatives. A strong background in applied machine learning, programming skills, and experience with technologies such as Tensorflow and PyTorch are essential. Candidates should have over 12 years of experience and knowledge of Agentic AI, contributing code in a collaborative setting.

Qualifications

• 12+ years of industry experience in applied Machine Learning.
• 2-3+ years working with LLMs and novel GenAI technologies.
• Strong programming and data engineering skills.
• Strong programming in Scala / Python / Java / C++ or equivalent; data engineering skills.
• Deep understanding of ML best practices, algorithms and domains (genAI, viral AI, NLP, CV).
• Experience with AgenticAI, TensorFlow, PyTorch, Kubernetes.

Responsibilities

• Define and execute on the long-term ML technical vision.
• Serve as a technical leader and mentor to other engineers.
• Drive and deliver large-scale, multi-quarter ML initiatives.
• Work with large scale structured and unstructured data.
• Collaborate with cross-functional partners to refine requirements and quantify impact.
• Work with trust defense and platform teams to tackle fraud landscape changes.
• Hands-on develop, productionize, and operate ML models and pipelines at scale.
• Examples include anomaly detection models and risk evaluation models.

Skills

Applied Machine Learning

Agentic AI

Data Engineering

Scala

Python

Java

C++

Education

Bachelor’s, Master’s or PhD in CS/ML or related field

Tools

Tensorflow

PyTorch

Kubernetes

Kubernetes

Job description

Remote - USA

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:

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. Trust Engineering is responsible for the technology vision and development of a complex stack that runs on every key interaction on the platform. Trust Engineering is at the forefront of AI and ML innovation, helping develop novel techniques and advancing the state-of-art in Machine Learning to continually build and maintain trust across our platform.

The Difference You Will Make:

As a senior technical individual contributor, you will partner closely with our leaders across the broader technical organization helping design, execute and deliver in a complex and collaborative roadmap of Trust engineering efforts that will require collaboration across many parts of the organization and many parts of Airbnb. Although you will be at one of our highest levels of seniority, all individual contributors at Airbnb are Software Engineers which means we expect you to be hands on and contribute code.

A Typical day:

• Define and execute on the long-term ML technical vision and strategy for the Trust organization, identifying key investments, architecting scalable solutions, and championing best practices that advance the state-of-the-art in production ML systems.
• Serve as a technical leader and mentor to other ML and software engineers across the organization, providing guidance on complex architectural and modeling challenges, and raising the overall technical bar.
• Drive and deliver large-scale, multi-quarter ML initiatives that span multiple teams, influencing roadmaps and ensuring alignment between platform and product
• Work with large scale structured and unstructured data, build and continuously improve cutting edge Machine Learning models for Airbnb product, business and operational use cases.
• Work collaboratively with cross-functional partners including software engineers, product managers, operations and data scientists, identify opportunities for business impact, understand, refine, and prioritize requirements for machine learning models, drive engineering decisions, and quantify impact.
• Work closely with other trust defense and platform teams to tackle the changing landscape of fraud attacks.
• Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases.
• Examples include: Anomaly detection models, ML models for continuous risk evaluation, Multimodality and Agentic AI

Your Expertise:

• 12+ years of industry experience in applied Machine Learning
• 2-3+ years working with LLMs and novel GenAI technologies. Proficiency and proven experience on Agentic AI (frameworks, orchestration, architecture and productionization).
• A Bachelor’s, Master’s or PhD in CS/ML or related field
• Strong programming (Scala / Python / Java/ C++ or equivalent) and data engineering skills
• Deep understanding of Machine Learning best practices (eg. training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (eg. gradient boosted trees, neural networks/deep learning, optimization) and domains (eg. genAI, Agentic AI, natural language processing, computer vision, personalization and recommendation, anomaly detection)
• Experience with these technologies: AgenticAI, Tensorflow, PyTorch, Kubernetes,
• Industry experience building end-to-end Machine Learning and Agentic infrastructure and/or building and productionizing Machine Learning models
• Exposure to architectural patterns of a large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models)
• Experience with test driven development, familiar with A/B testing, incremental delivery and deployment.
• Experience with the Trust and Risk domain is a plus.

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: [e-mail] . Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process.

We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application.

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.