Machine Learning Research Engineer Intern
1 month ago
Job Summary
SAIC Cambridge is seeking exceptional interns to participate in a 6-month research program starting in July 2024. The successful candidates will collaborate with researchers and engineers in a world-class cross-disciplinary research center, focusing on publishing research in top conferences, filing patents, and contributing to commercial tech transfers.
Key Responsibilities
- Conduct cutting-edge research to develop state-of-the-art solutions to existing problems and propose novel research challenges considering real-world case studies in AI.
- Develop high-quality code with detailed documentation to support reproducible research in local and international research communities in AI.
- Publication in top-tier conferences and journals, such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, AAAI, ACL, InterSpeech, etc.
Requirements
- Currently studying for a PhD in Computer Science, Engineering, Mathematics, or a related discipline.
- Efficiency in elementary topics in mathematics (calculus, probability, statistics, linear algebra, and optimization) and computer science (algorithms, data structures, parallel/distributed computing).
- Experience in one or more general-purpose programming languages, including Python, Java, C, and C++.
- At least one first-author publication in top conferences and journals such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, AAAI, InterSpeech, EMNLP, ACL, MobiComm, etc.
Desirable Skills
- Experience and demonstrated output on Foundation Models research involving LLMs and/or Diffusion models.
- Experience in software engineering and development in a professional environment.
- Experience with distributed GPU implementation of ML algorithms and on-device implementation of ML algorithms.
- Experience in one or more of SAIC-Cambridge topics of interest, including Future Interaction Lab, Embedded AI Lab, and Machine Learning/Data Intelligence Lab.
Contract Type: 6-month internship
Job Location: Cambridge, UK
Hybrid Working: Standard working week will be 3 days onsite and 2 days working from home if preferred
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