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Lidar Data Processing Jobs in British Columbia (NOW HIRING)

CA$155K - CA$190K/yr

Develop and maintain highly scalable data processing pipelines for data curation, annotation ... Experience working with multi‑modal data (Lidar, Camera, etc). * Experience with robotics systems.

Experience with survey geospatial tools and processes (GPS data collectors, processing of LiDAR or photogrammetry scans) is a strong asset * Canadian UAV Pilot Certificate (Advanced preferred) is an ...

Lidar Data Processing information

See British Columbia salary details

$10

$25

$68

How much do lidar data processing jobs pay per hour?

As of Aug 28, 2026, the average hourly pay for lidar data processing in British Columbia is $25.43, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $25.96 per hour, depending on experience, location, and employer.

What is a lidar data processing?

A Lidar Data Processing job involves handling, analyzing, and interpreting Lidar (Light Detection and Ranging) data to generate accurate 3D models, maps, or other spatial information. Professionals in this role clean and filter raw point cloud data, classify terrain features, and extract meaningful insights for applications like mapping, forestry, urban planning, and autonomous navigation. They use specialized software and algorithms to enhance data quality and ensure precision. This job requires expertise in geospatial analysis, data visualization, and often programming skills to automate processes.

What are some common challenges faced in lidar data processing?

Professionals in Lidar Data Processing often encounter challenges such as managing large datasets, ensuring data accuracy, and resolving discrepancies caused by environmental factors like vegetation or buildings. You may need to develop tailored workflows to efficiently process and clean raw lidar data, as well as work closely with project managers and survey teams to meet tight deadlines. Staying updated with advancing software tools and processing techniques is also key, as technology in this field evolves rapidly. Addressing these challenges requires both technical proficiency and strong problem-solving skills, making the work both rewarding and dynamic.

What are the key skills and qualifications needed to thrive in lidar data processing?

To thrive in Lidar Data Processing, you need strong skills in geospatial analysis, data accuracy, and the ability to work with 3D point cloud data, often supported by a degree in geography, GIS, or a related field. Familiarity with software such as ArcGIS, LAStools, and CloudCompare, as well as experience with lidar sensors and data formats, is highly valued, and certifications in remote sensing or GIS can be advantageous. Attention to detail, analytical thinking, and effective communication are crucial for interpreting data and collaborating with multidisciplinary teams. These skills enable you to ensure the precise processing, quality control, and delivery of critical spatial information for industries like mapping, engineering, and environmental management.

What are popular job titles related to Lidar Data Processing jobs in British Columbia?

For Lidar Data Processing jobs in British Columbia, the most frequently searched job titles are:

What job categories do people searching Lidar Data Processing jobs in British Columbia look for?

The top searched job categories for Lidar Data Processing jobs in British Columbia are:

Infographic showing various Lidar Data Processing job openings in British Columbia as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $52,900 per year, or $25.4 per hour.

Software Engineer, ML Infrastructure

On-site

Serve Robotics
Internet and IT • 51 - 200 employees

CA$155K - CA$190K/yr

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

Join to apply for the Software Engineer, ML Infrastructure role at Serve Robotics .

This range is provided by Serve Robotics. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$155,000.00/yr - $190,000.00/yr

At Serve Robotics, we’re reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. It’s designed to take deliveries away from congested streets, make deliveries available to more people, and benefit local businesses. The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles, Miami, Dallas, Atlanta and Chicago while doing commercial deliveries. We’re looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity.

Who We Are

We are tech industry veterans in software, hardware, and design who are pooling our skills to build the future we want to live in. We are solving real‑world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end‑to‑end user experience. Our team is agile, diverse, and driven. We believe that the best way to solve complicated dynamic problems is collaboratively and respectfully.

As a Software Engineer on the Machine Learning (ML) Infrastructure team, you will help design, build, and maintain our petabyte‑scale data and ML platform that powers data partnerships, ML research, and autonomy engineering. You will build and improve our data discovery capabilities and integrate with 3rd party annotation platforms. By collaborating with members of the autonomy and ML teams you will help us refine how we organize various data attributes and classifications. This role plays a pivotal role in helping the team leverage data from our rapidly expanding fleet of thousands of robots.

Responsibilities
  • Develop and maintain highly scalable data processing pipelines for data curation, annotation, search and ML feature extraction.
  • Build data discovery features for the platform.
  • Create and maintain search features such as natural language querying.
  • Develop and maintain our orchestration and scheduling systems.
  • Maintain and evolve our data schemas such as unified data attribute system, scenario tagging and management.
  • Build integrations with annotation providers to efficiently review large‑scale data pre‑annotations.
  • Collaborate with autonomy engineers to collect feedback, improve documentation, and run tutorials on platform features.
Qualifications
  • BS or MS in computer science with a focus in data engineering and/or machine learning.
  • 3+ years of industry experience building, running and improving large‑volume data processing, feature extraction, data annotation workflows.
  • Experience building data mining and search capabilities.
  • Experience with both Python and SQL is required.
  • Solid understanding of data distributions and their impact on ML models.
  • Hands‑on experience and good understanding of LLMs, VLMs, embeddings, vector databases.
  • Experience with data annotation providers such as CVAT, LabelBox, LabelStudio, etc.
What Makes You Stand Out
  • Experience with integrating cloud inference platforms for LLMs/VLMS (ChatGPT, Gemini, etc).
  • Experience working with multi‑modal data (Lidar, Camera, etc).
  • Experience with robotics systems.
  • Experience optimizing large‑scale vector databases.
Seniority level

Mid‑Senior level

Employment type

Full‑time

Job function

Engineering and Information Technology

Industries

Technology, Information and Internet

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