Description:Client is seeking a PhD graduate in Computer Science, Electrical Engineering, Mechanical Engineering, or a related engineering discipline to work on Agentic AI systems for mobility.
The successful candidate will conduct cutting-edge research at the intersection of large language models (LLMs), agentic AI, multi-agent systems, world models, reinforcement learning, and knowledge distillation, enabling efficient AI deployment across cloud, edge, and embedded platforms for intelligent mobility and autonomous systems
What you'll be doing:
- Develop innovative solutions that advance AI/ML systems for mobility services
- Design and develop multi-agent AI systems capable of collaboration, negotiation, planning, and task execution
- Research LLM-based reasoning and autonomous planning for long-horizon decision making
- Develop teacher-student learning frameworks to transfer reasoning, planning, and collaboration capabilities from large foundation models to compact edge models
- Prototyping frameworks and algorithms in Python using tools such as AutoGen, LangChain, or custom orchestration layers
- Publish Client research in top-tier conferences and journals and generate high-impact intellectual property and patents
Requirements:- Ph.D. in Computer Science, Electrical Engineering, Mechanical Engineering, or a related engineering discipline with a focus on AI / Machine Learning
- Research experience in Generative AI, Agentic AI, and AI Safety and Alignment
- Research experience with Foundational (LLMs, VLMs, and other large-scale AI architectures), including fine-tuning, evaluation, and application to domain-specific tasks
- Strong programming skills in Python and common libraries (e.g., TensorFlow, Pytorch, etc.)
- Ability to engage in general research activities such as defining problems and issues to be addressed, finding, and using research data, and being able to make recommendations and findings in writing and presentations
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