Position Summary

At the Samsung AI Center-Cambridge, our teams work closely to develop innovate machine learning (ML) algorithms and systems, with the overarching objective to deliver state-of-the-art efficient AI models across Samsung consumer devices. To this end, we focus on high-impact projects that balance research and commercial outcomes. Our group conducts research on on-device and edge-based ML systems, focusing on model/system and hardware/software co-design, adaptive inference methods, robotic systems, and the optimized on-device deployment of large language models (LLMs) and multimodal visual language models (VLMs).

Our team is characterized by its diverse backgrounds and expertise, ranging from pure machine learning and mobile/embedded systems to computer architecture and robotics, with strong emphasis on combining excellent research skills with hands-on development abilities. This diversity has enabled us to develop groundbreaking cross-stack ML systems and algorithms. Throughout our projects, we maintain strong ties with close-to-product teams, contributing to commercialization goals and ensuring our research has a tangible impact for Samsung through successful tech transfers and numerous patent applications. At the same time, our work is consistently and widely recognized, with multiple papers published in top-tier international conferences and journals.

Role and Responsibilities

As a Research Scientist you will:

• Research and development of world models that enable AI agents to understand, simulate, and reason about complex environments.

• Design and run experiments at the frontier of model-based learning, contributing to foundational research that shapes how AI agents perceive and interact with the world.

• This role requires a strong background in machine learning, a passion for tackling open-ended research problems, and the drive to build systems.

• Contribute to research and commercialization efforts for Samsung AI Centre in areas including on-device LLM and VLMs, adaptive inference methods, and mobile ML systems.

• Conduct cutting-edge research within the existing group's agenda as well as contribute towards shaping it.

• Collaborate closely with cross-functional product teams, as well as on-site research teams, to integrate ML solutions into consumer devices.

• At the core of our efforts is innovation, as you will design groundbreaking machine learning algorithms and systems that extend the capabilities of current technology.

• You will translate research findings into practical applications, contributing to the commercialization of AI technologies across millions of Samsung devices.

• Additionally, you will prepare comprehensive documentation, research papers, and contribute towards patent applications.

• You will work alongside team members with varying levels of experience in a collaborative and continuous learning environment, with a strong focus on individual development throughout our work. In our group, we highly value and require an open and cooperative mindset and seek determined individuals who are committed to obtaining new knowledge and producing high-quality work.

Skills and Qualifications

Education and experience:

• PhD in CS/EE or related research experience in academia or industry

• We will consider various levels of experience in relevant research areas

Key Skills:

• Experience with ML frameworks (PyTorch, TensorFlow, JAX) and efficient ML (incl. quantization, pruning, sparsification, distillation, etc.)

• Experience with deployment on embedded/mobile devices (such as smartphones, with mobile CPU, GPU, NPU)

• Experience with distributed and multi-GPU training at scale

• Fluency in Python, C/C++ and GNU Linux

• Proficiency in code version control, Git and GitHub

• Experience in working as member of a team

• Solid publication record of papers in top-tier venues, such as NeurIPS/ICLR/ICML/MobiCom/MobiSys/ICCAD/MLSys

Any of the following skills will also be positively considered:

• Experience in real-world mobile system deployment

• Research experience in efficient Generative AI, including language, visual or multimodal tasks. This includes different aspects of the pipeline, from data and preprocessing to large model adaptation, fine-tuning and on-device optimization.

• Android operating system and Android app development

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