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LeadFull-timeRustMachine LearningData ScienceAIMLNLP
Salary Range
$153,000 - $207,000 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a Staff Engineer to join our Communication Products team at Airbnb. This role focuses on building a first-class messaging experience, bringing together guests and hosts across the world. You will lead the technical vision for ML-powered messaging features and define the technical strategy for integrating ML capabilities into Airbnb's messaging products.
Key Responsibilities
- →Design, build, and operate the systems that serve ML models within the messaging stack
- →Write and review technical designs that solve large, open-ended problems at the intersection of ML and product engineering
- →Partner with ML, data science, and product teams to identify high-value opportunities
- →Collaborate with other engineers and cross-functional partners across Messaging, Trust & Safety, Localization, and Platform organizations
- →Mentor, guide, advocate, and support the career growth of individual contributors
- →Establish engineering standards for ML integration across the messaging surface
Requirements
- ✓9+ years of relevant engineering hands-on work experience
- ✓Bachelors, Masters, or PhD in CS or related field
- ✓Demonstrated experience building and shipping ML-powered product features in production environments
- ✓Exceptional architecture abilities and experience with architectural patterns of large, high-scale applications
- ✓Familiarity with NLP/NLU techniques and large language models
- ✓Shipped several large-scale projects with multiple dependencies across teams
- ✓Technical leadership and strong communication skills
- ✓Experience operating distributed, real-time systems at scale
- ✓Experience with real-time messaging systems or event-driven architectures
- ✓Familiarity with ML infrastructure at scale
- ✓Prior work on trust & safety, content moderation, or internationalization in a messaging context
- ✓Experience with LLM-based product features
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