Senior Machine Learning Engineer, Trust

Airbnb
San Francisco
Workplace: RemoteFull timeUSD 200,000 - 235,000Function: Data Science & Machine LearningExperience: 5-10 yearsEducation: bachelorsSkills: ["Comfort with ambiguity","Bias toward action","Collaboration","Communication","Code quality"]

Build and deliver end-to-end ML projects for Airbnb’s Trust Frontier AI team, protecting the community from fraud across online and offline domains. You’ll prototype ambiguous problems, create and productionize batch and real-time ML pipelines, and develop AI agents that automate trust decisions. Partner with product, data science, and front-line defense teams to validate impact via experiments, guardrails, benchmarks, and evaluation harnesses—shipping reliable, measurable improvements at scale.

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FursaFursa
Airbnb
Airbnb
3 days ago

Senior Machine Learning Engineer, Trust

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 5 hours agoStatus: Live
Reposted: similar role first listed 3 months ago

Job Summary

Build and deliver end-to-end ML projects for Airbnb’s Trust Frontier AI team, protecting the community from fraud across online and offline domains. You’ll prototype ambiguous problems, create and productionize batch and real-time ML pipelines, and develop AI agents that automate trust decisions. Partner with product, data science, and front-line defense teams to validate impact via experiments, guardrails, benchmarks, and evaluation harnesses—shipping reliable, measurable improvements at scale.
Location: San Francisco
Workplace: Remote
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Frame and prototype ML and agentic solutions for trust and safety problems without an established approach.
  • •Design, build, and productionize end-to-end ML pipelines for both batch and real-time use cases, including feature engineering, training, evaluation, and deployment.
  • •Develop and improve abuse behavior detection that generalizes across defenses.
  • •Design, launch, and iterate on AI agents that automate trust decisions, including orchestration, tool interfaces, and quality guardrails.
  • •Build benchmarks and evaluation harnesses, instrument decision quality, and partner with front-line teams to validate impact through experiments and holdouts.

Pay and Benefits

Salary: USD 200,000 - 235,000
Equity and Bonus:Equity

Key Requirements

  • •5-10 years of industry experience applying machine learning and productionizing models at scale.
  • •1-2+ years of hands-on experience with LLMs and GenAI technologies, including agentic frameworks, orchestration, and evaluation.
  • •Strong programming skills in Python (required) and familiarity with Scala, Java, or equivalent.
  • •Solid ML fundamentals including feature engineering, model selection, and concepts like A/B testing and training/serving skew minimization, plus experience with ML algorithms such as gradient boosted trees, neural networks, and transformers.
  • •Experience with ML frameworks and tooling (e.g., TensorFlow, PyTorch or equivalent) and building end-to-end batch and real-time ML pipelines, plus ML/LLM evaluation methodology.
Experience:5-10 years
Education:Bachelor's in CS/ML or a related field
Skills:Comfort with ambiguityBias toward actionCollaborationCommunicationCode quality
Tech Stack:PythonScalaJavaTensorFlowPyTorchLLMsGenAITransformersDeep learningAgentic frameworksOrchestrationA/B testingMachine learning pipelines

Company Brief

Airbnb
Online marketplace that connects travelers with hosts offering short-term lodging, experiences, and long-term stays. Facilitates booking, payments, and reviews while providing tools for hosts to manage listings globally.
Industry: Online Marketplaces
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: San Francisco, United States
Founded: 2008
WebsiteLinkedIn