Applications for this job are now closed
The Samsung Research and Development Institute, UK (SRUK) conducts cutting-edge applied research on foundations and challenges of artificial intelligence (AI) to develop state-of-the-art solutions for real-world large-scale problems.
The department often disseminates the research outputs in local and international research communities such as in research seminars, and top-tier conferences and journals.
The accepted candidates will have the opportunity to work on diverse fields of AI as a member of the AI Research Team, including machine learning, deep learning and natural language processing (NLP).
Role and responsibilities
As a forward-thinking company, we are at the forefront of innovation and seek an individual with a passion for pushing the boundaries of AI:
- Cutting-edge research to develop state-of-the-art solutions to existing problems and/or propose novel research challenges considering real-world case studies in AI.
- Development of high-quality code with detailed documentation to support reproducible research in local and international research communities in machine learning.
- Review the state-of-the-art research papers and develop prototype solutions.
- Publication in top-tier conferences and journals, such as NeurIPS, ICML, ICLR, EMNLP, CVPR, ICCV, ECCV, AAAI, ACL, IEEE TPAMI, IEEE TNNLS, IJCV, and JMLR.
Skills and qualifications
Required skills
- Academic Background: Pursuing a PhD in ML/AI, Computer Science/Engineering, or related fields.
- Mathematical and Computer Science Fundamentals: Proficiency in calculus, probability, statistics, linear algebra, optimization, algorithms, data structures, and parallel/distributed computing.
- Machine Learning and Deep Learning: Strong understanding of ML and DL concepts.
- Research and Implementation:
- First-author publications in top ML/AI conferences/journals (e.g., ICML, NeurIPS, ICLR, EMNLP, CVPR, ECCV, IEEE TPAMI, AAAI).
- Hands-on experience in at least one of these areas: Generative AI, Parameter-Efficient Fine-Tuning (PEFT), Foundation Models, Large Language Models (LLMs), Data/Model Privacy, Prompting Methods, and Model Compression (e.g., Quantization, Pruning, Knowledge Distillation).
- Technical Experience:
- Familiarity with Linux environments.
- Proficiency in programming languages like Python, Java, or C++.
- Experience with ML libraries such as PyTorch, SciKit, and NumPy
- Soft Skills: Excellent communication, teamwork, problem-solving, and debugging abilities.
Desirable skills
- Advanced Expertise:
- Text Generation, PEFT-LoRA, Autoregressive Models, and Prompting Methods.
- Training/Fine-tuning Foundation Models and LLMs.
- Data/Model Privacy and Model Compression techniques.
- Retrieval Augmented Generation.
Minimum of 3 days per week onsite and 2 days working from home.
