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Hourly Lidar Data Processing Jobs in California (NOW HIRING)

Waymo

Staff Software Engineer, Privacy

Mountain View, CA · On-site

$251K - $310K/yr

... camera/Lidar data at the edge (on-vehicle) and in the cloud before it enters our training sets ... Experience working with large-scale data processing frameworks (e.g., Flume, MapReduce, etc..) and ...

Rivian

Staff ML Engineer, Perception

Palo Alto, CA · On-site

$228 - $285/hr

... lidar data. Responsibilities * Drive and deliver production-grade, high-quality, scalable auto ... Rivian is committed to ensuring that our hiring process is accessible for persons with disabilities.

Chloeta

GIS Specialist

Sacramento, CA · On-site +1

$40 - $50/hr

The GIS Specialist assists with enterprise geodatabase management, GIS data processing, quality ... Managing Lidar Data Using Mosaic Datasets. * Map Design Fundamentals. * Creating Prediction ...

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Hourly Lidar Data Processing information

What is hourly LiDAR data processing?

Hourly LiDAR data processing refers to the analysis and interpretation of LiDAR (Light Detection and Ranging) data on an hourly basis. This involves collecting raw LiDAR data, cleaning and filtering the data, and generating useful outputs such as 3D models or elevation maps. The role is important in industries like surveying, forestry, construction, and autonomous vehicles, where up-to-date spatial information is crucial for decision-making. Professionals in this field use specialized software to process and manage large datasets efficiently. The hourly aspect usually means that workers are paid by the hour and may handle tasks as projects or data come in.

What are some common challenges faced in hourly LiDAR data processing roles and how can they be addressed?

Hourly Lidar data processing professionals often encounter challenges such as managing large volumes of raw data, ensuring data quality and accuracy, and meeting tight turnaround times. Dealing with inconsistencies in data due to varying environmental conditions or equipment calibration can also be demanding. To address these, it’s helpful to follow standardized workflows, use automated tools for data cleaning and classification, and maintain clear communication with the data collection team. Staying organized and collaborating closely with colleagues can streamline processing and help ensure deliverables meet client expectations.

What are the key skills and qualifications needed to thrive as an hourly LiDAR data processing specialist, and why are they important?

To thrive in Hourly Lidar Data Processing, you need a solid understanding of geospatial data concepts, attention to detail, and experience with Lidar data formats, often supported by coursework or training in geography, GIS, or remote sensing. Proficiency in specialized software such as LAStools, ArcGIS, QGIS, and familiarity with point cloud processing systems is typically required. Analytical thinking, problem-solving, and strong organizational skills help individuals stand out in managing large datasets efficiently. These skills are crucial for ensuring accurate, timely, and reliable data outputs that support mapping, surveying, and environmental analysis projects.

What is the difference between Hourly Lidar Data Processing vs Lidar Data Analyst?

AspectHourly Lidar Data ProcessingLidar Data Analyst
Primary RoleProcessing raw Lidar data into usable formatsAnalyzing processed Lidar data for insights
Skills & CertificationsGIS, remote sensing, data processing toolsGIS, data analysis, reporting skills
Work EnvironmentField data collection, office processingOffice-based data analysis and reporting
Industry UsageSurveying, mapping, environmental studiesUrban planning, infrastructure, research

Hourly Lidar Data Processing focuses on converting raw Lidar data into usable formats, requiring technical skills in data processing. Lidar Data Analysts interpret and analyze this processed data to generate insights. While both roles require knowledge of GIS and remote sensing, processing is more technical and hands-on, whereas analysis emphasizes interpretation and reporting.

What are the most commonly searched types of Lidar Data Processing jobs in California?

The most popular types of Lidar Data Processing jobs in California are:

What cities in California are hiring for Hourly Lidar Data Processing jobs?

Cities in California with the most Hourly Lidar Data Processing job openings:

Hourly Lidar Data Processing jobs near you
Infographic showing various Hourly Lidar Data Processing job openings in California as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Drone Pilot for AI Training and Data Collection

TSMG

San Francisco, CA • On-site

Full-time

Re-posted 17 days ago

Job description

We are seeking an experienced and highly skilled Drone Pilot to assist in the development and training of AI models, specifically in the areas of computer vision, sensor fusion, and autonomous navigation. The ideal candidate will be responsible for collecting high-quality data in real-world environments, contributing to the optimization of AI algorithms that power autonomous systems.

As a Drone Pilot for AI & Autonomous Systems Training, you will operate advanced drones to capture data essential for training and validating AI models that power autonomous navigation, object detection, and decision-making systems.
Key Responsibilities:
  • Pilot drones equipped with high-resolution cameras, LiDAR, thermal imaging, and other sensors to collect diverse datasets used for training AI algorithms, particularly for autonomous navigation, computer vision, and sensor fusion.
  • Capture data in various real-world conditions (e.g., urban, rural, industrial, challenging weather conditions) to expose AI systems to a wide range of environments and scenarios.
  • Execute complex drone missions with precise data collection objectives, such as aerial mapping, 3D reconstruction, obstacle detection, and object tracking.
  • Collaborate closely with AI engineers, machine learning specialists, and autonomous systems teams to ensure data collection aligns with the specific requirements of AI model training.
  • Perform post-flight data quality checks and initial preprocessing to ensure the datasets are ready for use in training AI models.
  • Operate drones in both manual and autonomous modes, supporting AI-driven flight operations where drones rely on onboard algorithms for navigation and decision-making.
  • Adhere to Federal Aviation Administration (FAA) and local aviation regulations governing drone operations, ensuring the safe and compliant conduct of all drone missions.
  • Oversee the maintenance, calibration, and troubleshooting of drones and onboard sensors to ensure the highest standards of performance and reliability.
Qualifications:
  • Commercial drone pilot certification (FAA Part 107 or equivalent), with additional certifications in safety or advanced drone technologies considered a plus.
  • Proven track record as a drone pilot, with significant experience in collecting data for industrial, research, or AI-focused applications.
  • Expertise in flying drones equipped with advanced sensors such as LiDAR, thermal cameras, RGB cameras, and multispectral sensors.
  • Familiarity with the nuances of autonomous flight, sensor integration, and machine learning workflows, especially those that involve real-time data processing.
  • Strong understanding of how drone-collected data is used for AI training, including its role in training AI for perception, navigation, and decision-making.
  • Experience in using software for flight planning, such as Pix4D, DroneDeploy, or similar platforms, and geospatial data analysis tools.
  • Familiarity with machine learning concepts, especially those related to computer vision (e.g., image segmentation, object detection, and tracking) and autonomous navigation systems.
  • Basic understanding of geospatial data processing, photogrammetry, and 3D reconstruction techniques for AI applications.
  • Strong attention to detail with a commitment to ensuring the highest quality of data collection and analysis.
  • Excellent communication and collaboration skills, with the ability to work in multidisciplinary teams.
We would be happy to get to know you and your skills better and see how we can support each other's growth.

Please apply and let's meet!
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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