Software Engineer, Airbnb - New Grad

Airbnb•San Francisco, CA

4d•Hybrid

About The Position

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. Our Engineering org is a diverse, fast-moving group of teams working across Payments, Trust, Marketing, Relevance & Personalization, and more. Together, we're tackling some of the hardest problems in tech: search relevance at global scale, fraud prevention, seamless payments, and fueling growth — all while delivering a product experience that feels effortless and beautiful. We're also at the forefront of integrating AI and machine learning into our products — from personalized search experiences to intelligent trust and safety systems — and we're looking for curious engineers who are excited to grow alongside this technology. If you're energized by engineering that creates real-world human connection — and by the idea that your code will be experienced by millions of people around the world — you'll feel right at home here.

Requirements

Recent graduates (Bachelor's or Master's) with less than 1 year of full-time professional experience.
Strong foundation in Computer Science fundamentals — data structures, algorithms, design patterns, and systems thinking.
Proficiency in one or more of: Java, Scala, Ruby, Ruby on Rails, C++, SQL, HTML/CSS, JavaScript, Objective-C, Swift (iOS), or Kotlin (Android).
Foundational awareness of AI/ML concepts — such as supervised learning, model evaluation, or working with APIs backed by large language models (LLMs) — gained through coursework, personal projects, or internships.
An understanding of responsible AI principles — including fairness, privacy, and safety — and a curiosity about how these apply to real-world product development.

Nice To Haves

Familiarity with Python and common AI/ML libraries (e.g., NumPy, scikit-learn, or PyTorch) is a plus.
Experience integrating cloud-based AI services or LLM APIs.
Leadership experience, community involvement, or teaching/mentoring.

Responsibilities

Play a vital role in building, supporting, and refining the products and systems that make Airbnb’s mission possible.
Directly contribute to high-quality, reliable experiences for our global community—whether you’re fixing bugs, launching well-defined features, or enhancing existing components.
Contribute to AI-powered features, applying foundational knowledge of machine learning concepts and modern AI tools to build smarter, more personalized experiences for our hosts and guests.
Clearly communicate challenges and collaborate with teammates across functions to help drive projects forward with transparency and trust.
Foster a sense of belonging by actively seeking feedback, sharing your own learnings, and supporting the onboarding of new team members.
Uphold Airbnb’s commitment to excellence by following best practices, delivering tasks autonomously, and continually improving your technical skills.
Attend team syncs to discuss priorities, share progress, and surface any blockers with transparency.
Dive into coding—fixing bugs, developing features, or refining APIs and components—while applying best practices for code quality, error handling, and testability.
Leverage AI-assisted development tools (e.g., Claude Code or similar) to accelerate your workflow and improve code quality.
Participate in design or code reviews, ask clarifying questions, and apply feedback to improve your work.
Work closely with cross-functional partners like product managers and designers to ensure your tasks align clearly with broader goals.
Dedicate time to expanding your technical knowledge through documentation, mentorship, or internal knowledge-sharing sessions.
Stay current on AI/ML developments relevant to your team's domain — whether that's recommendation systems, natural language understanding, or AI safety practices.
Seek guidance from managers or tech leads when tackling unfamiliar problems.
Contribute to team activities, such as onboarding new hires (e.g., being an onboarding buddy), sharing observations from the hiring process, or joining in cultural events focused on diversity, inclusion, and innovation.
Share updates on your progress and next steps, highlighting challenges or learnings.