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We're seeking a creative problem-solver who's excited about architecting novel deep learning solutions for multimodal search and retrieval. You'll work on advancing the state-of-the-art in vision-language models and multimodal embeddings, while developing efficient and scalable algorithms for cross-modal retrieval. Your role will involve creating innovative solutions for multimodal ranking and relevance, ultimately building the next generation of multimodal search systems that can understand and process information the way humans do.
Key job responsibilities
- As an Applied Scientist, you will leverage your technical expertise and experience to demonstrate leadership in tackling large complex problems, setting the direction and collaborating with applied scientists and engineers to develop novel algorithms and modeling techniques to enable timely, relevant and delightful search experiences.
- Develop state-of-the-art multimodal search technology, including training novel retrieval and ranking models for images/videos, scaling models and optimizing performance, partnering with engineering to deploy and debug model performance in production, and building and scaling quality training data sets.
- 1+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- PhD in Computer Science/Engineering, Machine Learning, or related field with specialties in information retrieval, recommendation system, or multimodal learning.
- Hands on experience with Visual LLMs
- Publications at peer-reviewed NLP/ML conferences (e.g. ACL, EMNLP, NAACL, NeurIPS, ICLR, ICML, AAAI, CVPR)
- Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field
- Experience with distributed systems, web services, or large-scale data processing.
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