About the job
Qualcomm AI Research is looking for world-class researchers in artificial intelligence to join our team. Members of our global team form a multi-disciplinary core research group within Qualcomm which spans software, hardware, and systems, and we contribute technology deployed worldwide by partnering with our business teams across mobile, compute, automotive, cloud, and IOT. We also perform and publish state-of-the-art research on a wide range of topics in artificial intelligence, ranging from general theory to techniques that enable deployment on resource-constrained devices. We are dedicated to pushing the boundaries of AI across Generative AI, LLM and Multi-Modal Foundation Models, Reasoning, Reinforcement Learning, Agentic AI, and Autonomy, with a strong emphasis on efficient on-device intelligence. Please see our AI focus page at https://qualcomm.com/ai for more details.
Responsibilities
Conduct cutting-edge research in efficient generative AI: LLMs and Multi-Modal Foundation Models, LLM Reasoning, Reinforcement Learning, Agentic AI and others.
Lead efforts in transitioning research into production-ready solutions, enabling real-world applications and commercial impact.
Develop creative solutions with consideration of practical challenges on devices
Implementation and evaluation of possible solutions in both simulation and on-device environments
Contribute to Qualcomm’s strategic initiatives in efficient AI and embedded intelligence.
Publish in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ACL, EMNLP).
Qualifications
Minimum
Proven research excellence demonstrated by publications in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ACL, EMNLP).
Deep expertise in Generative AI, Multi-Modal Foundation models, Vision Language Models, Reasoning, Reinforcement Learning, and Agentic AI.
Hands-on experience with model development pipelines, including training, fine-tuning, evaluation, and optimization.
Preferred
PhD in Computer Science, Electrical Engineering, or related fields or MS with 4+ years of AI research, or related work experience
Research Experience in developing vision language models for understanding and generation.
Understanding of efficient architectures suitable for on-edge deployment, experience in on-device AI deployment on mobile or edge devices
Familiar with model optimization techniques such as pruning, quantization and distillation.