Qualcomm Technologies, Inc. is looking to solve the problem of advancing artificial intelligence research and development, specifically in areas such as Generative AI, LLM and Multi-Modal Foundation Models, Reasoning, Reinforcement Learning, Agentic AI, and Autonomy.
Requirements
- 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, LLMs, Multi-Modal Foundation models, LLM Reasoning, Reinforcement Learning, and Agentic AI.
- Hands-on experience with model development pipelines, including training, fine-tuning, evaluation, and optimization.
- Experience in LLM efficiency research such as efficient attention, inference acceleration, or KV cache compression
- Experience in on-device AI deployment on mobile or edge devices
- Familiar with model optimization techniques such as quantization and distillation.
Responsibilities
- Conduct cutting-edge research in efficient generative AI: LLMs and Multi-Modal Foundation Models, LLM Reasoning, Reinforcement Learning, Agentic AI and others.
- Provide technical leadership in research and applied projects and guide research directions to best support company objectives.
- Mentor interns, junior researchers and engineers, fostering collaboration, growth and excellence in a dynamic R&D environment.
- 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.
Other
- Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
- OR PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
- 6+ months of experience developing and/or optimizing machine learning models, systems, platforms, or methods.
- PhD with 4+ years in Computer Science, Electrical Engineering, or related fields or MS with 8+ years of AI research, or related work experience.
