Research and Implementation of the research for future mobility services
Prototyping frameworks and algorithms in Python using tools such as AutoGen, LangChain, or custom orchestration layers
Developing innovative solutions that advance AI/ML systems for mobility services
Conducting applied research in Agentic AI, including agent design, orchestration strategies, tool integration, and communication protocols
Identifying research gaps and propose novel solutions to enhance performance, reliability, and adaptability of agent-based systems
Conducting research on AI safety and alignment topics
Requirements
ph.d.
python
tensorflow
pytorch
llms
generative ai
Ph.D. in Computer Science, Electrical Engineering, Mechanical Engineering, or a related engineering discipline with a focus on AI / Machine Learning
Proficient programming skills in Python and common libraries (e.g., TensorFlow, Pytorch, etc.)
Research experience with Foundational (LLMs, VLMs, and other large-scale AI architectures), including fine-tuning, evaluation, and application to domain-specific tasks
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
Research experience in Generative AI, Agentic AI, and AI Safety and Alignment