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Autonomous Driving Mapping Jobs (NOW HIRING)

Isuzu

$87K - $123K/yr

Probabilistic filtering, sensor fusion, SLAM, GNSS/IMU, HD maps, image and point cloud processing ... Hands-on deployment of autonomous driving algorithms or DL models on embedded systems * Control ...

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Autonomous Driving Mapping information

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$6

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$39

How much do autonomous driving mapping jobs pay per hour?

As of Sep 12, 2026, the average hourly pay for autonomous driving mapping in the United States is $21.37, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $21.63 per hour, depending on experience, location, and employer.

What is autonomous driving mapping?

Autonomous driving mapping refers to the creation and maintenance of detailed digital maps that are used by self-driving vehicles to understand and navigate their environment safely. These maps contain high-definition information about road layouts, traffic signs, lanes, intersections, and other critical features. Autonomous vehicles rely on these maps, in combination with real-time sensor data, to make driving decisions and ensure accuracy in positioning. The mapping process involves collecting data from multiple sources, such as cameras, LiDAR, GPS, and other sensors, and integrating it into a comprehensive, up-to-date map. These maps are essential for the safe and efficient operation of autonomous vehicles.

What are the key skills and qualifications needed to thrive in autonomous driving mapping, and why are they important?

To excel in Autonomous Driving Mapping, you need expertise in geospatial data analysis, computer vision, and a background in computer science, engineering, or a related field. Proficiency with mapping software such as GIS tools, HD map creation platforms, LiDAR data processing, and programming languages like Python or C++ is typically required. Strong problem-solving skills, attention to detail, and effective teamwork are critical soft skills for this role. These abilities ensure the creation of accurate, high-definition maps that are essential for safe and reliable autonomous vehicle navigation.

How does the autonomous driving mapping role typically collaborate with engineering and data science teams?

In an Autonomous Driving Mapping role, collaboration with engineering and data science teams is essential for integrating detailed map data with vehicle perception and navigation systems. Mapping specialists work closely with engineers to ensure that map updates and features are compatible with the vehicle’s hardware and software platforms. They also partner with data scientists to analyze sensor data, validate map accuracy, and continually improve localization algorithms. Regular cross-functional meetings and agile workflows help maintain alignment and accelerate problem-solving across these teams.

What is the difference between Autonomous Driving Mapping vs Autonomous Vehicle Sensor Technician?

AspectAutonomous Driving MappingAutonomous Vehicle Sensor Technician
CredentialsGIS, mapping software, CAD skillsElectronics, sensor calibration certifications
Work EnvironmentField data collection, office-based mappingGarage, lab, on-vehicle sensor testing
Industry UsageAutonomous vehicle development, mapping companiesVehicle manufacturers, service centers
Search/Comparison IntentUnderstanding roles in autonomous vehicle techSensor installation and maintenance in autonomous vehicles

Autonomous Driving Mapping specialists focus on creating detailed maps and spatial data essential for autonomous vehicle navigation. In contrast, Autonomous Vehicle Sensor Technicians handle the installation, calibration, and maintenance of sensors on autonomous vehicles. Both roles are vital in the autonomous vehicle industry but differ in skills, work environment, and responsibilities.

Infographic showing various Autonomous Driving Mapping job openings in the United States as of September 2026, with employment types broken down into 80% Full Time, and 20% Temporary. Highlights an 100% In-person job distribution, with an average salary of $44,459 per year, or $21.4 per hour.

New Grads 2027 - Software Engineer, Algorithm

San Jose, CA • On-site

WeRide.ai
IT Services • 501 - 1,000 employees
Learn more about WeRide.aiexternal

$120K - $165K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 4 days ago

Job description

Established in 2017, WeRide (NASDAQ: WRD) is a leading global commercial-stage company that develops autonomous driving technologies from Level 2 to Level 4 and is the world's first publicly listed autonomous vehicle (AV) company. Its business footprint now spans more than 60 cities across 13 countries. Powered by the intelligent, versatile, and highly adaptable WeRide One platform, the company provides autonomous driving products and services ranging from Level 2 to Level 4, addressing mobility, logistics, and urban services.
What You May Work On:
  • Prediction: Design models that forecast the behaviors and intentions of surrounding vehicles, pedestrians, and other dynamic agents, enabling safer driving decisions
  • Mapping & Localization: Explore algorithms for vehicle localization and environment representation, leveraging maps, onboard sensors, and learning-based methods to ensure reliable positioning in diverse conditions
  • Planning & Control: Contribute to motion planning and decision-making modules that support safe, efficient, and human-like driving behaviors, as well as robust vehicle control algorithms
  • Simulation Core: Build simulation platforms with realistic sensor modeling and 3D environment reconstruction to accelerate the validation and development of autonomous driving technologies
Qualifications:
  • MS/PhD degree in Robotics, Computer Science, Physics, Computer Vision, Graphics, Machine Learning, Automation or equivalent practical experience, with an expected graduation date between December 2026 and June 2027.
  • Proficient in C++ and/or Python with knowledge of its latest features.
  • Strong analytical and problem-solving skills.
  • Excellent communication, and cross-functional team collaboration abilities.
  • Passion for innovation in the autonomous vehicle industry.
Bonus Points:
  • Published research presented at leading machine learning or robotics conferences such as NeurIPS, CVPR, ICML, ICLR, ICCV, ECCV, IROS, or ICRA.
  • Proficient in machine learning frameworks, such as TensorFlow or PyTorch.
  • Experience in open-source competitions or challenges related to autonomous driving.
Team Introductions:
  • Prediction Team:
The Prediction team liaises with the perception team upstream and the planning and control team downstream. We develop diverse deep learning models using perceptual information to forecast potential future behaviors of nearby obstacles. In scenarios lacking sufficient data, the prediction team generates predictions and supplements through analysis of scene features and logical reasoning.
  • Planning and Control Team:
The main goal of the planning and control team is to find safe driving strategies in complex autonomous driving environments. We ensure safe, efficient navigation by designing algorithms for route planning and vehicle control to respond to dynamic conditions. Our work integrates sensor data and predictive models to make real-time decisions for smooth and reliable autonomous driving.
  • Mapping and Localization Team:
The mapping and localization team is responsible for high-definition mapping and high-precision localization systems for our entire autonomous fleet. We provides down-stream modules, e.g. perception, prediction, planning and control, with accurate and real-time positioning as well as detailed geometric and semantic information of the surroundings, to help the autonomous vehicle navigate the world. A variety of underlying technologies are employed to build the mapping and localization systems, including multi-sensor fusion, visual/lidar SLAM, 3D computer vision and deep learning.
  • Sim Core Team:
The Sim Core group focuses on developing the core simulation capabilities necessary to support company-wide AV development and validation. This team will work on our overall simulation strategies, sensor simulation for perception, AI simulation for prediction, planning and control, full-stack simulation, and the generation and editing of 3D worlds.
$120,000 - $165,000 a year
Your base pay is one part of your total compensation package. For this position, the reasonably expected pay range is between $120,000 - $165,000 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package.
What Happens Next:
 
We'll take a few weeks to review all applications. If we'd like to move forward with you, we'll reach out to arrange the next steps, which may include an online assessment, a call with a recruiter, and 4-5 interviews with your future colleagues to better inform our decision.
 
During the interview process, we aim to learn more about your skills, experiences, and motivators. Many of our questions will focus on understanding how you might operate here at WeRide. Please note that, due to the high volume of applications we receive, we're unable to offer individual feedback during the interview process.
 
We recognize that interviewing for a new role is significant, and we appreciate you considering WeRide as the next step in your career. Our Recruiting Team is here to support you throughout the interview process. Come join us and apply today!
 

WeRide.ai offers competitive salary depending on the experience. Employee benefits include:
Premium Medical, Dental and Vision Plan (No cost from employees or their families)
Free Daily Breakfast, Lunch and Dinner
Paid vacations and holidays
401K plan
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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