Machine Learning Engineering Intern (PhD)
AirbnbUnited StatesPosted 2 March 2026
Job Description
<div class="content-intro"><p><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">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.</span></p></div><p> </p>
<p><strong>The community you will join:</strong></p>
<p>Airbnb is seeking a Machine Learning Engineer Intern for our 2026 Summer Intern Program</p>
<p>Machine Learning at Airbnb is a diverse and dynamic field, with teams working on various aspects of the ML landscape. We are using ML to tackle various challenges in search ranking, payments, fraud prevention, discrimination, and growth all while maintaining a beautiful experience. We love to contribute to the community, by publishing blog posts and scientific papers at ML Conferences. Some of our publications can be found on Medium: <a href="https://medium.com/airbnb-engineering/tagged/machine-learning">https://medium.com/airbnb-engineering/tagged/machine-learning</a></p>
<p>Search Relevance and Personalization team is responsible for building search ranking algorithms and the personalization platform that serves multiple product surfaces. The team consists of 30+ ML Engineers working on different aspects of relevance and personalization. The team is very much experimentation oriented and runs frequent A/B tests to improve the relevance of the product surfaces they power. The team is also very much applied research oriented and regularly publishes work at KDD, CIKM and WSDM Conferences.</p>
<p> </p>
<p><strong>The difference you will make:</strong></p>
<p>As an intern, you’ll be integrated into a team where you’ll drive a project from end-to-end that aligns with your technical interest and goals. </p>
<p>The intern project will revolve around exploring how new advancements in AI agents can be applied to Airbnb search and discovery experience.</p>
<p> </p>
<p><strong>The intern experience:</strong></p>
<p>As an intern, you’ll be integrated into a team where you’ll contribute to challenging projects. Your manager, team, and our incredible employee community will strive to be superhosts to you during the summer. We provide the support, mentorship, fun, and real world experience needed to accelerate your learning and make a real impact on our product, as Airbnb revolutionizes connection, belonging, and travel. You can expect to:</p>
<ul>
<li>Own and drive a capstone project from beginning to end</li>
<li>Collaborate with multiple team members to achieve project milestones</li>
<li>Communicate with stakeholders across different teams to provide project updates</li>
<li>Seek and provide feedback throughout the internship</li>
<li>Actively participate in and contribute to the Engineering org and broader Airbnb community</li>
</ul>
<p> </p>
<p><strong>Your expertise:</strong></p>
<p>This internship opportunity is for <strong>Doctorate students</strong> with at least 1 semester of school remaining after the internship (<strong>expected graduation after December 2026</strong>).</p>
<ul>
<li>Studying Computer Science or a related field</li>
<li>Knowledge of AI, especially large language model (LLM) fundamentals including fine tuning, data synthesis, reinforcement learning, etc.</li>
<li>Expertise of building large scale ReAct style AI agents. </li>
<li>Proficient in Python and other open source LLM libraries like Huggingface</li>
<li>Publications in top Machine Learning and NLP conferences are a big plus.</li>
<li>Leadership position, AI community involvement, and or teaching/mentoring experience is a plus!</li>
<li>Work authorization for employment in the United States is required</li>
</ul>
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<p><strong>Your Location:</strong></p>
<p>This position is US - Remote Eligible. The role may include occas ... (truncated, view full listing at source)
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