Senior Staff Machine Learning Engineer, Trust

at Airbnb
USD 244,000-305,000 per year
SENIOR
✅ Remote

Tech Stack

A/B Testing @ 7 AI @ 6 API @ 6 Agentic AI @ 4 Algorithms @ 4 Computer Vision @ 4 Data Engineering @ 7 Data Pipelines @ 6 Deep Learning @ 7 GenAI Generative AI @ 6 Java @ 7 Kubernetes @ 4 LLM Machine Learning @ 8 NLP PyTorch @ 4 Python @ 7 Scala @ 7 TensorFlow @ 4

Details

Airbnb's Trust Engineering team develops technology to protect the community and platform from fraud, including monetary loss, compromised accounts, spam and scams, fake inventory, theft, property damage, and personal safety risks. The team also works on user onboarding and screening, identity, and reputation. Trust Engineering advances AI and machine learning techniques to build and maintain trust across the platform.

As a senior technical individual contributor, you will partner with leaders across the technical organization to design, execute, and deliver complex Trust engineering initiatives. Individual contributors at Airbnb are hands-on Software Engineers who contribute code.

Responsibilities

  • Define and execute the long-term machine learning technical vision and strategy for the Trust organization.
  • Identify key investments, architect scalable solutions, and champion best practices for production machine learning systems.
  • Serve as a technical leader and mentor to machine learning and software engineers across the organization.
  • Provide guidance on complex architectural and modeling challenges and raise the overall technical bar.
  • Drive and deliver large-scale, multi-quarter machine learning initiatives spanning multiple teams.
  • Influence roadmaps and ensure alignment between platform and product teams.
  • Work with large-scale structured and unstructured data to build and continuously improve machine learning models for product, business, and operational use cases.
  • Collaborate with software engineers, product managers, operations, and data scientists to identify opportunities for business impact, refine and prioritize machine learning requirements, drive engineering decisions, and quantify impact.
  • Work with Trust defense and platform teams to address the changing landscape of fraud attacks.
  • Hands-on develop, productionize, and operate machine learning models and pipelines at scale for batch and real-time use cases.
  • Work on applications including anomaly detection, continuous risk evaluation, multimodality, and Agentic AI.

Requirements

  • 12+ years of industry experience in applied machine learning.
  • 2–3+ years of experience working with LLMs and novel generative AI technologies.
  • Proven experience with Agentic AI frameworks, orchestration, architecture, and productionization.
  • Bachelor's, Master's, or PhD in Computer Science, Machine Learning, or a related field.
  • Strong programming and data engineering skills in Scala, Python, Java, C++, or equivalent.
  • Deep understanding of machine learning best practices, including training-serving skew minimization, A/B testing, feature engineering, and feature and model selection.
  • Knowledge of algorithms and domains including gradient-boosted trees, neural networks and deep learning, optimization, generative AI, Agentic AI, natural language processing, computer vision, personalization and recommendation, and anomaly detection.
  • Experience with Agentic AI, TensorFlow, PyTorch, and Kubernetes.
  • Industry experience building end-to-end machine learning and Agentic AI infrastructure and/or building and productionizing machine learning models.
  • Exposure to architectural patterns for large-scale software applications, including well-designed APIs, high-volume data pipelines, efficient algorithms, and models.
  • Experience with test-driven development and familiarity with A/B testing, incremental delivery, and deployment.
  • Experience with the Trust and Risk domain is a plus.

Location

This position is remote eligible in the United States. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed with the manager. The employee must live in a state where Airbnb, Inc. has a registered entity. If the position is employed by another Airbnb entity, the recruiter will advise which states are eligible.

Benefits

The role may be eligible for bonus, equity, benefits, and Employee Travel Credits. Airbnb states that base pay depends on factors including training, transferable skills, work experience, business needs, and market demands.

Inclusion and Accessibility

Airbnb encourages qualified individuals from diverse backgrounds to apply and provides a disability-inclusive application and interview process. Reasonable accommodation is available by contacting [email protected].

Compensation

Base pay range: $244,000–$305,000 USD per year.

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