Company:
Job Area:
Engineering Group, Engineering Group > Machine Learning Engineering
General Summary:
About US
We are Qualcomm AI Research that are advancing AI to make its core capabilities – perception, reasoning, and action – ubiquitous across devices. Our mission is to make breakthroughs in fundamental AI research and scale them across industries. By bringing together some of the best minds in the field, we're pushing the boundaries of what's possible and shaping the future of AI. Welcome to visit our website at AI Research Areas | Intelligence on Devices | Qualcomm.
Key Responsibilities
- Design and develop system architecture for intelligent memory, learning, and personalization in on-device AI agents. Create techniques for contextual information utilization, enabling adaptive and personalized user interactions.
- Research and implement algorithms for learning from user experiences and environmental cues, transforming them into actionable insights and knowledge, developing technologies to enhance knowledge understanding and reasoning.
- Optimize model performance under the agentic AI use cases, working on advanced finetuning, reinforcement learning, and RLHF techniques, like RFT, GRPO, ARPO, and/or other modern policy optimization algorithms.
- Develop and optimize models for on-device deployment, including agentic RAG-based solutions, LLM fine-tuning strategies, domain adaptation, and so on.
- Build and maintain agentic workflows for autonomous AI systems. Build robust evaluation frameworks for measuring and improving model performance.
- Collaborate with cross-functional teams to identify opportunities and implement AI solutions.
Required Qualifications
- MS with 2+ years of relevant experience, PhD, or equivalent practical experience is preferred. Major in Computer Science, Computer Engineering, Artificial Intelligence, Electrical Engineering or related field.
Preferred Skills
- In-depth knowledge in deep learning (DL) and machine learning (ML).
- Excellent programming skills in Python, with proficiency in PyTorch.
- Familiarity with LLM techniques, including RAG, prompting, post-training.
- Familiarity with advanced RL & RLHF techniques, like PPO, GRPO, ARPO and so on.
- Mandatory experience in Natural Language Processing (NLP), particularly in information extraction, LLM prompt engineering, and LLM fine-tuning.
- Research and development experience in LLM memory, knowledge representation, and reasoning systems.
- Experience with on-device AI and lightweight model development.
- Excellent problem-solving and analytical skills.
- Effective communication and teamwork skills.
- Experience using AI coding assistants such as Claude code, Codex, or Cursor is a plus.
Minimum Qualifications:
• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
Master's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
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