Isuzu Technical Center of America, Inc is looking to solve the problem of building AI systems to support fleet decision making in routing, dispatching and energy optimization for autonomous driving
Requirements
- Proficient in Python and ML frameworks (e.g., PyTorch, TensorFlow, CUDA)
- Strong interest in LLMs, agentic AI, autonomous systems, or fleet intelligence
- Understanding of reinforcement learning, multi-agent systems, or planning and optimization algorithms is a plus
- Familiarity with geospatial data, vehicle telemetry, or routing logic is a plus
- Experience with any simulation tools (CARLA, SUMO, Nvidia Omniverse tools, RoboSuite or Flow etc.) is a plus
- Foundational understanding of machine learning, deep learning, LLM and optimization
- Basic knowledge of autonomous driving, routing and logistic operations is a plus
Responsibilities
- Build AI systems to support fleet decision making in routing, dispatching and energy optimization
- Development of methods and approaches using state-of-art approaches such as Sim2Real
- Hands-on exposure to cutting-edge AI systems for future mobility and transportations
- Cross-functional collaboration with ISUZU global teams and partners
- Development of methods and approaches for autonomous driving
- Build AI systems for fleet intelligence
- Development of methods and approaches for routing and logistic operations
Other
- Currently enrolled in a Bachelor's, Master's, or PhD program in Computer Science, Machine Learning, Robotics, or a related field
- Strong academic standing (e.g., 3.5 GPA or equivalent recommended)
- Cross-functional collaboration with ISUZU global teams and partners
- Part-time internship
- Seniority level: Internship
