Principal Scientist, -Device Personalization

Position: Principal Scientist, On-Device Personalization

Job Location

Mountain View, CA

Job Category Job Type

Full-Time

Job #

402630

Job Department

Artificial Intelligence Center

Lab

Summary:

Samsung’s AI Center (AIC) located in Mountain View, California, is currently recruiting outstanding scientists for the Language and Personal Intelligence lab. Our goal is to perform research and development with direct impact on future Samsung products reaching hundreds of millions of users worldwide. We are focused on pushing the state-of-the-art and practice in natural language and knowledge intelligence.

Position Summary: We are looking for an experienced research leader to drive product-focused research in On-Device Personalization, leveraging LLMs and machine learning to shape next-generation AI-driven user experiences. This role will focus on ambient intelligence, ensuring seamless, adaptive, and privacy-preserving personalization at the edge. You will craft the vision, lead innovation, and collaborate across research, engineering, and product teams to push the boundaries of AI-driven user interaction.

• Influence the future of on-device AI and personalization at scale.
• Work with a team of world-class researchers and engineers.
• Drive groundbreaking AI research into real-world impact.
• Competitive compensation, benefits, and growth opportunities.

If you are excited about crafting the future of AI-driven, personalized experiences, apply now and be part of an innovative, forward-thinking team.

Position Responsibilities:

• Lead and define the vision for on-device personalization and ambient intelligence, driving research that enables LLM-powered, user-centric experiences
• Spearhead research and development efforts in LLM-driven personalization, context-aware AI, and on-device machine learning to enhance user experiences
• Collaborate closely with cross-functional teams, including product managers, research scientists, and platform engineers, to align cutting-edge AI research with real-world product applications
• Architect and optimize on-device LLM models, ensuring efficient performance under computational constraints while maintaining personalization accuracy and privacy
• Translate research advancements into scalable, production-ready AI solutions, integrating seamlessly with consumer applications and devices
• Build and mentor a high-performing team of engineers and researchers, fostering a culture of innovation, collaboration, and technical excellence
• Engage with the broader research community, contribute to publications, and drive thought leadership in on-device AI, personalization, and ambient intelligence

Required Skills:

• PhD (preferred) or Master’s degree in Machine Learning, Natural Language Processing (NLP), AI, or a related field. or equivalent combination of education, training, and experience
• 14+ years of technical leadership experience, driving AI/ML research into real-world product applications
• Proven experience in LLM-based product experiences, personalization, and on-device AI
• Strong understanding of on-device machine learning, federated learning, and computational efficiency optimizations
• Expertise in deep learning frameworks (PyTorch, Tensor Flow, JAX) and NLP model architectures (Transformer-based models, Distillation, LoRA, Quantization, etc.)
• Exceptional collaboration and communication skills, with a track record of partnering across research and product teams
• A passion for ambient intelligence and the future of intuitive, AI-powered experiences

Special Attributes:

• Experience with edge computing, mobile AI frameworks (Core ML, Tensor Flow Lite, ONNX Runtime, etc.), and privacy-preserving AI
• Contributions to top AI/ML conferences (NeurIPS, ICML, ACL, CVPR, etc.)
• Track record of building and scaling AI-powered personalization solutions

Our total rewards programs are designed to motivate and engage exceptional talent. The base pay range for roles at this level is listed below, but may be higher or lower in other states due to geographic differentials in the labor market. Within the base pay range, individual rates depend on a number of factors—including the role’s function and location as well as the individual’s knowledge, skills, experience, education and training.

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