Research Staff
Mixedbread · San Francisco, CA · Remote
Infrastructureremote
At a glance
Highlights
- Lead applied research rethinking search for large models via Omni platform.
- Design next-gen late-interaction and multimodal retrieval models.
- Explore LLM-augmented search and real-world agentic evaluations.
What they offer
- Competitive compensation + equity
- 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
Ideal candidate
IR researcher passionate about pushing search beyond single-vector methods, eager to translate novel retrieval ideas into real product impact and share findings openly.
Requirements
- Experience in information retrieval, embeddings, or related fields
- Advanced degree (PhD/Master's) or equivalent experience with impactful research projects
- Proficiency in Python and ability to implement models from scratch
- Passion for advancing search beyond single-vector similarity methods
- Broad understanding of the ML lifecycle: algorithms, training, data, efficiency
- Strong written and verbal communication skills
- visa sponsorship
- Visa sponsorship + relocation support
Lab profile
About Mixedbread
Building next-generation multimodal, transformer-native information retrieval systems for AI applications.
What they build
- AI search API
- Embedding and retrieval models
- Developer dashboards and interactive playgrounds
Known for
- Multimodal information retrieval
- Multilingual search across 100+ languages
- LLM-augmented and agentic search
- High-performance search infrastructure
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