Autonomous Driving Kit Software Engineer

ISUZU NORTH AMERICA CORPORATION•Sunnyvale, CA

1d•Onsite

About The Position

This position supports/leads the development of Autonomous Driving software modules such as Perception/Localization, Planning/Prediction, or Control. The role involves focusing on a single module initially and expanding into multiple modules based on project demands and organizational priorities. Key activities include verifying developed software, conducting vehicle tests on test tracks or public roads, and running simulation evaluations. The engineer will design, implement, and optimize software systems that enable safe, reliable, and intelligent driving behavior. This includes working on both rule-based and data-driven approaches for the autonomous driving software stack, which may involve onboard stack development, Machine Learning (ML) model, and data pipeline developments for ML training. The role requires close collaboration with Isuzu US and Japan teams, leading autonomous driving partner companies, and reputed research institutes on the development and validation of autonomous systems. Depending on the experience level, the position might work under close supervision from more senior staff and follow established procedures, or independent judgment is required and the individual can guide junior staff. Joining this team offers the opportunity to 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, and contribute meaningfully to the future of transportation and mobility autonomy through global collaboration across U.S. and Japan technical teams.

Requirements

Master’s degree in Computer Science, Electrical Engineering, Robotics, Data science or related fields.
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.
Strong analytical, problem-solving, and critical thinking skills.
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.
Depending on the experience level, practical experience in real-time testing, tuning, and closed-loop validation.
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).

Nice To Haves

PhD preferred.
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.
(Preferred: Perception/Localization Engineer) Solid understanding of computer vision and point cloud processing.
(Preferred: Perception/Localization Engineer) Solid understanding of deep learning architectures, including CNNs and Transformers.
(Preferred: Perception/Localization Engineer) Knowledge of GNSS/IMU error models and sensor calibration.
(Preferred: Perception/Localization Engineer) Experience with multi-sensor fusion (camera, LiDAR, radar).
(Preferred: Perception/Localization Engineer) Practical experience implementing or adapting Graph-SLAM systems (e.g., g2o, GTSAM, Ceres Solver).
(Preferred: Perception/Localization Engineer) 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).
(Preferred: Planning/Prediction Engineer) Practical experience developing ML model of motion prediction or time series data analysis.
(Preferred: Planning/Prediction Engineer) Solid understanding of deep learning architectures, including RNNs and Transformers.
(Preferred: Planning/Prediction Engineer) Experience using HD maps, and basic understanding of map data format.
(Preferred: Planning/Prediction Engineer) Basic understanding of optimization solver (e.g. QP Solver).
(Preferred: Planning/Prediction Engineer) Solid understanding of feasibility of planned trajectory under vehicle dynamic limits.
(Preferred: Planning/Prediction Engineer) Knowledge of Minimum Risk Maneuver (MRM) concept and algorithm.
(Preferred: Control Engineer) Solid understanding of classical control theory including PID controller.
(Preferred: Control Engineer) Hands-on experience of tuning control performance by changing control parameters in test vehicle.
(Preferred: Control Engineer) Solid understanding of Model Predictive Control (MPC).
(Preferred: Control Engineer) Basic understanding of vehicle dynamics (e.g. bicycle model) and actuator modeling constrains and latency (steering, throttle, brake, powertrain).
(Preferred: Control Engineer) Practical experience with integrated control, localization, and sensor fusion systems closed-loop testing (both simulation and on-road) is a plus.
(Preferred: Control Engineer) 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 (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 (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 (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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