Machine Learning Researcher

Responsibilities

• 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 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.

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

Additional Skills

• 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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