Autonomous Driving Kit Software Engineer

We are looking to hire an Engineer I or Engineer II. This position is based in Plymouth, MI, and compensation is aligned with this designated work location.

JOB SUMMARY Supports/leads development of Autonomous Driving software such as Perception/Localization, Planning/Prediction or Control modules. Focuses on a single module to progressively expand into multiple modules as project demands and organizational priorities evolve. Verifies the developed software, conducts vehicle tests on test track or public road and runs simulation evaluations.

Designs, implements, and optimizes software systems that enable safe, reliable, and intelligent driving behavior. Works on both rule-based and data driven approaches for autonomous driving software stack which may include onboard stack development, Machine Learning (ML) model, and data pipeline developments for ML training. Works closely with Isuzu US and Japan teams, leading autonomous driving partner companies, and reputed research institutes on the development and validation of autonomous Depending on the experience level, position might work under close supervision from more senior staff and follow established procedures or independent judgment is required and can guide junior staffs.

WHY JOIN US?

Work with industry-leading partners and institutions on cutting-edge AI for future mobility and logistics solutions

Gain hands-on experience in simulation, validation, and deployment of production driven AI systems

Exposure to global collaboration across U.S. and Japan technical teams

Opportunity to make a meaningful contribution to the future of transportation and mobility autonomy PRINCIPAL DUTIES & RESPONSIBILITIES
35% 1. Develops software for Autonomous Driving software stack (Perception/Localization, Planning/Prediction or Control).30% 2. Collaborates on tasks with partnership organizations (including both Isuzu group companies and external companies) by participating in discussion/negotiation and reviewing documents/source code.
15% 3. Analyzes driving log data and prepares data pipeline for ML model training.
10% 4. Evaluates Autonomous Driving system performance by executing simulation/emulation.
5% 5. Develops advanced technology or research in Autonomous Driving algorithm.
5% 6. Supports vehicle testing to verify and evaluate the Autonomous Driving system.
7. Performs miscellaneous job-related duties as assigned.

ORGANIZATIONAL RELATIONSHIPS

Reports to:

Supervisor, Autonomous EDUCATION, EXPERIENCE & TRAINING Master’s degree in Computer Science, Electrical Engineering, Robotics, Data science or related fields. PhD preferred.

Minimum one year of working experience in data analysis, robotics, programming, or automotive systemsKNOWLEDGEFundamentals of autonomous driving, robotics, signal processing, and data science

Academic background in autonomous systems, ML (DL/RL/VLM/LLM), vehicle dynamics, or simulation

Depending on the experience level, understanding of ADAS/AD architecture, module interfaces, and production software

Depending on the experience level, familiarity with ISO 26262 and functional safety standards

Depending on the experience level, knowledge of end-to-end autonomous driving systems

Domain-specific knowledge (based on role):

Perception/Localization:
Probabilistic filtering, sensor fusion, SLAM, GNSS/IMU, HD maps, image and point cloud processing, DL(CNN and Transformer)
Planning/Prediction:
Path/trajectory planning, motion prediction, optimization, MRM, DL(RNN and Transformer)
Control:
Classical/MPC control, vehicle dynamics, actuator modeling, RL for control tuning

SKILLS AND ABILITIES

Strong analytical, problem-solving, and critical thinking

Effective communication and teamwork, both independently and collaboratively

Proficiency in Python and C++Experience with ML frameworks (PyTorch, Tensor Flow), simulation tools, and robotic middleware (ROS
2)
Depending on the experience level, familiarity with Docker, Bazel, CAN communication, and profiling tools (Nsight, nvprof, perf)
Hands-on deployment of autonomous driving algorithms or DL models on embedded systems

Control-specific tools: MATLAB-Simulink/Stateflow Depending on the experience level, practical experience in real-time testing, tuning, and closed-loop validation

Job Specific

Skills:

Experience with data transmission through Controller Area Network (CAN)
Hands-on experience with TensorRT, CUDA, cuDNN, or custom GPU kernel optimization

Understanding of ADAS/AD system architecture including interface between modules and production software…