Autonomous Driving Kit Software Engineer
Isuzu North America
•
Plymouth, MI
0
0
0
0
Not Applicable
Posted April 3, 2026
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Responsibilities
Commitments
Responsibilities
- 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.
- 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.
- Performs miscellaneous job-related duties as assigned.
- ORGANIZATIONAL RELATIONSHIPS
- Reports to: Supervisor, Autonomous
Commitments
This position will start in either Plymouth, Michigan or Sunnyvale, California , with a planned relocation to our Sunnyvale, California office.
35% 1.
15% 3.
5% 6.
The employee must be able to access, enter, and retrieve data using a computer.
This is primarily a sedentary position in a controlled office environment which requires only occasional reaching, stooping, and lifting of office files, reports or records, typically weighing 5 lbs. or less.
Requires occasional light lifting (5-25 lbs).
Must be able on rare occasions to bend, crawl, climb, crouch, kneel and reach above shoulder level in the performance of job duties.
Must be able to work in hot and cold weather extremes.
Position requires up to 5% travel, mostly domestic.
Occasional overnight or weekend trips; rare chance of international travel.
We are looking for up to a Senior level engineer.
Not Met Priorities
What still needs stronger evidence
Requirements
- 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 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, 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)
- 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.
- 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.
- The employee must be able to access, enter, and retrieve data using a computer.
- Must be able on rare occasions to bend, crawl, climb, crouch, kneel and reach above shoulder level in the performance of job duties.
- Must be able to work in hot and cold weather extremes.
Preferred Skills
- 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)
- Control-specific tools: MATLAB-Simulink/Stateflow
- Depending on the experience level, practical experience in real-time testing, tuning, and closed-loop validation
- Hands-on experience with TensorRT, CUDA, cuDNN, or custom GPU kernel optimization
- Familiarity with profiling tools (Nsight Systems, nvprof, perf)
- (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.
- 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
Education
- (Not required) – Master’s degree in Computer Science, Electrical Engineering, Robotics, Data science or related fields.
- (Not required) – PhD preferred.
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
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.
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 systems
KNOWLEDGE
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 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, 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
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
PHYSICAL STANDARDS
The employee must be able to access, enter, and retrieve data using a computer. This is primarily a sedentary position in a controlled office environment which requires only occasional reaching, stooping, and lifting of office files, reports or records, typically weighing 5 lbs. or less. Requires occasional light lifting (5-25 lbs). Must be able on rare occasions to bend, crawl, climb, crouch, kneel and reach above shoulder level in the performance of job duties. Must be able to work in hot and cold weather extremes.
Position requires up to 5% travel, mostly domestic. Occasional overnight or weekend trips; rare chance of international travel.
We are looking for up to a Senior level engineer. The pay scale for an Engineer I in this role is $85,315 to $108,777. The pay scale for an Engineer II in this role is $94,695 to $120,737. The pay scale for a Senior Engineer in this role is $105,118 to $134,025. The base salary will be determined based on a variety of factors, such as relevant experience and education.
Exceptional Perks That Go Beyond the Basics
Join a workplace that invests in your well-being—mind, body, and future:
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
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.
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 systems
KNOWLEDGE
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 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, 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
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
PHYSICAL STANDARDS
The employee must be able to access, enter, and retrieve data using a computer. This is primarily a sedentary position in a controlled office environment which requires only occasional reaching, stooping, and lifting of office files, reports or records, typically weighing 5 lbs. or less. Requires occasional light lifting (5-25 lbs). Must be able on rare occasions to bend, crawl, climb, crouch, kneel and reach above shoulder level in the performance of job duties. Must be able to work in hot and cold weather extremes.
Position requires up to 5% travel, mostly domestic. Occasional overnight or weekend trips; rare chance of international travel.
We are looking for up to a Senior level engineer. The pay scale for an Engineer I in this role is $85,315 to $108,777. The pay scale for an Engineer II in this role is $94,695 to $120,737. The pay scale for a Senior Engineer in this role is $105,118 to $134,025. The base salary will be determined based on a variety of factors, such as relevant experience and education.
Exceptional Perks That Go Beyond the Basics
Join a workplace that invests in your well-being—mind, body, and future:
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