Autonomous Driving Kit Software Engineer

ISUZU NORTH AMERICA CORPORATION•Plymouth, MI

1d•$85,315 - $134,025

About The Position

We are looking for up to a Senior level engineer. This position will start in either Plymouth, Michigan or Sunnyvale, California, with a planned relocation to our Sunnyvale, California office. 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

Requirements

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 systems
Fundamentals 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
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, TensorFlow), 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

Nice To Haves

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 development
Knowledge of ISO 26262 or functional safety standards
Familiarity with profiling tools (Nsight Systems, nvprof, perf)
Hands-on experience deploying Autonomous Driving algorithms or DL models, in real-time systems or automotive environments (on embedded or automotive-grade hardware)
Basic understanding of End-to-end autonomous driving system (e.g. BEV feature based, Vision-Language-Action Model) (Preferred: Perception/Localization Engineer)
Understanding of probabilistic filtering (e.g., Kalman Filter, Particle Filter) and nonlinear optimization.
Solid understanding of computer vision and point cloud processing
Solid understanding of deep learning architectures, including CNNs and Transformers.
Knowledge of GNSS/IMU error models and sensor calibration.
Experience with multi-sensor fusion (camera, LiDAR, radar)
Practical experience implementing or adapting Graph-SLAM systems (e.g., g2o, GTSAM, Ceres Solver).
Experience using HD maps, lane-level localization, and map matching techniques.
(Preferred: Planning/Prediction Engineer)
Practical experience implementing path planner (e.g. Dijkstra, A algorithm) or trajectory planner (e.g. Frenet frame)
Practical experience developing ML model of motion prediction or time series data analysis
Solid understanding of deep learning architectures, including RNNs and Transformers
Experience using HD maps, and basic understanding of map data format
Basic understanding of optimization solver (e.g. QP Solver)
Solid understanding of feasibility of planned trajectory under vehicle dynamic limits
Knowledge of Minimum Risk Maneuver (MRM) concept and algorithm
(Preferred: Control Engineer)
Solid understanding of classical control theory including PID controller
Hands-on experience of tuning control performance by changing control parameters in test vehicle
Solid understanding of Model Predictive Control (MPC)
Basic understanding of vehicle dynamics (e.g. bicycle model) and actuator modeling constrains and latency (steering, throttle, brake, powertrain)
Practical experience with integrated control, localization, and sensor fusion systems closed-loop testing (both simulation and on-road) is a plus.
Experience in applying Reinforcement Learning (RL) to vehicle controller or controller parameter tuning is a plus.

Responsibilities

Develops software for Autonomous Driving software stack (Perception/Localization, Planning/Prediction or Control).
Collaborates on tasks with partnership organizations (including both Isuzu group companies and external companies) by participating in discussion/negotiation and reviewing documents/source code.
Analyzes driving log data and prepares data pipeline for ML model training.
Evaluates Autonomous Driving system performance by executing simulation/emulation.
Develops advanced technology or research in Autonomous Driving algorithm.
Supports vehicle testing to verify and evaluate the Autonomous Driving system.
Performs miscellaneous job-related duties as assigned.

Benefits

Comprehensive Health Coverage Medical, dental, vision, and fertility benefits to support you through every stage of life
Fertility & Family-Building Support through WIN Fertility: Includes Adoption & Surrogacy Benefits, WINMaternity, and PowerPause, offering up to $25,000 in lifetime benefits for fertility-related services such as IVF, IUI, and preconception support
Generous Time Off Enjoy a healthy work-life balance with paid vacation, 15 paid holidays annually, sick leave, parental leave, and MTO (Miscellaneous Time Off) for volunteering or a compelling personal need
Smart Retirement Planning Build long-term financial security with a 401(k) plan featuring a company match and an additional Annual Retirement Contribution (ARC)
Peace of Mind Company-paid Basic Life and AD&D Insurance, as well as Travel Insurance, so you're covered wherever life takes you
Wellness Program Access a variety of tools and resources designed to support your physical and mental well-being
Tuition Reimbursement Pursue continued education with financial support for job-related coursework, degree programs, and professional growth
Exclusive Employee Discounts Save on insurance, travel, entertainment, car purchases/rentals, retail purchases, and more

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