What are the responsibilities and job description for the Research Intern position at Mixedbread?
At Mixedbread, we believe search is the ultimate bottleneck for AI. Our mission is to build the next generation of multimodal information retrieval systems that can surface just the right context, no matter the format.
About The Role
As a Research Intern, you'll join our applied research lab and work directly with senior researchers on projects that push retrieval beyond its current limits. You'll gain hands-on experience in tackling real-world search problems, from late interaction models to LLM-augmented retrieval. Each internship is designed to produce a tangible output — such as a blog post, paper, or open-source release — while giving you deep exposure to both research and product impact.
What you'll do
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Join us in building the future of search.
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About The Role
As a Research Intern, you'll join our applied research lab and work directly with senior researchers on projects that push retrieval beyond its current limits. You'll gain hands-on experience in tackling real-world search problems, from late interaction models to LLM-augmented retrieval. Each internship is designed to produce a tangible output — such as a blog post, paper, or open-source release — while giving you deep exposure to both research and product impact.
What you'll do
- Own and execute a retrieval research project under the guidance of senior researchers
- Design, implement, and evaluate new approaches to information retrieval
- Explore multimodal search challenges across text, images, and beyond
- Investigate how LLMs can enhance or reshape retrieval pipelines
- Contribute to open science through papers, blog posts, or open-source models
- Provide feedback to help us continuously improve the internship programme
- Late Interaction: Next-generation fine-grained retrieval methods beyond ColBERT
- Omni-Modality: Designing truly multimodal retrievers
- LLM-Augmented Search: Studying how LLMs generate, rank, and consume retrieval results
- Evaluation: Creating evals that capture real-world, agentic use cases
- Data Work: Improving retrieval signals and datasets for stronger performance
- Interpretability: Understanding why retrieval models succeed or fail
- Currently enrolled in an undergraduate or graduate program
- Prior exposure to retrieval, embeddings, or adjacent domains (e.g., projects, papers, blog posts, or open source contributions)
- Proficiency in Python and ability to implement models from scratch
- Strong interest in Information Retrieval and its role in advancing AI
- Belief that single-vector similarity search is outdated, with enthusiasm for late interaction and beyond
- Collaborative mindset and willingness to learn from feedback
- Competitive internship compensation
- Close mentorship from a world-class team
- Comprehensive health, dental, and vision coverage
- Visa sponsorship relocation support
- Professional development budget
- Access to the best AI tools and subscriptions
- Team off-sites conference attendance
- Transportation support
- Wellness support, including gym membership and sports club subscriptions
- Food support
Apply for this position
Join us in building the future of search.
Autofill from resume
Upload your resume here to autofill fields.
Name *
Email *
Resume *
Click to upload or drag and drop
PDF, Word, Excel, or image file (max 10MB)
LinkedIn profile
Please provide a link to your LinkedIn profile.
GitHub profile
Please provide a link to your GitHub profile.
X profile
Please provide a link to your X profile.
What's one project or achievement you're proud of? *
What excites you about joining Mixedbread? *