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Remote Video Labelling Jobs in Chicago, IL (NOW HIRING)

Remote Video Labelling information

See Chicago, IL salary details

$39.1K

$77.8K

$132.9K

How much do remote video labelling jobs pay per year?

As of Aug 3, 2026, the average yearly pay for remote video labelling in Chicago, IL is $77,774.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,700.00 and $90,100.00 per year, depending on experience, location, and employer.

How much are data labelers paid?

Data labelers, including those working remotely in video labeling roles, typically earn between $10 and $20 per hour depending on experience, complexity of tasks, and the company. Pay rates can vary based on the platform, project scope, and whether the work is freelance or full-time employment.

How can I make 2000 a week working from home?

Remote video labelling jobs can pay varying rates, often between $10 and $20 per hour, depending on the company and project complexity. To earn $2,000 weekly, you would need to work approximately 100 hours at these rates, which may require high-volume or premium projects, strong attention to detail, and efficient use of annotation tools. Building experience and a good reputation can help access higher-paying opportunities in this field.

What is remote video labelling?

Remote video labelling is the process of watching video footage and accurately annotating or tagging objects, actions, or events within the video, all while working from a remote location, usually from home. This work is essential for training machine learning and AI models, particularly in fields like autonomous vehicles, security, and content moderation. Video labellers use specialized software to mark frames and provide metadata that helps computers understand visual information. Attention to detail and consistency are crucial in this job to ensure high-quality labelled data.

What are the key skills and qualifications needed to thrive as a Remote Video Labelling Specialist, and why are they important?

To thrive as a Remote Video Labelling Specialist, attention to detail, basic computer proficiency, and a high school diploma or equivalent are generally required. Familiarity with annotation tools, video editing software, and data labeling platforms is typically expected, with some roles preferring experience in machine learning or data management systems. Strong time management, focus, and effective communication skills help individuals excel in independent, deadline-driven environments. These skills ensure accurate data labeling, which is crucial for training high-quality AI and machine learning models.

Is data labeling work from home?

Remote video labelling jobs are often performed from home, allowing workers to complete tasks using a computer and internet connection. These roles typically require attention to detail, familiarity with labeling tools, and a flexible schedule, making them suitable for remote work environments.

What is a video labeling job?

A video labeling job involves reviewing and annotating video content to help train machine learning algorithms. Workers typically use specialized tools to add tags, identify objects, or categorize scenes, often working remotely with flexible schedules. Accuracy and attention to detail are important for this type of data annotation work.

What are some common challenges faced by remote video labelling professionals, and how can they be managed?

Remote video labelling professionals often encounter challenges such as staying focused during repetitive tasks, ensuring accuracy when identifying subtle visual details, and managing communication with team members across different time zones. To address these, it's helpful to set up a distraction-free workspace, take regular breaks to maintain concentration, and use collaborative tools to stay connected with supervisors and peers. Additionally, following established labelling guidelines and participating in quality assurance sessions can help maintain consistency and accuracy in your work.

What is the difference between Remote Video Labelling vs Remote Image Annotation?

AspectRemote Video LabellingRemote Image Annotation
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageAutonomous vehicles, surveillance, AI trainingObject detection, medical imaging, retail
Search & Comparison IntentUnderstanding differences in data labeling rolesUnderstanding differences in annotation tasks

Remote Video Labelling involves annotating video data frame-by-frame, often requiring temporal consistency, while Remote Image Annotation focuses on labeling individual images. Both roles are remote, require attention to detail, and are used in AI training across various industries. The main difference lies in the data type: videos versus images, with video labelling demanding more complex, time-sensitive annotations.

What are the most commonly searched types of Video Labelling jobs in Chicago, IL? The most popular types of Video Labelling jobs in Chicago, IL are:
What are popular job titles related to Remote Video Labelling jobs in Chicago, IL? For Remote Video Labelling jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Remote Video Labelling jobs in Chicago, IL look for? The top searched job categories for Remote Video Labelling jobs in Chicago, IL are:

AV Simulation Domain Expert (Sr. Principal) - US (Remote) or Chicago, IL

HERE Technologies

Chicago, IL • On-site, Remote

$170K - $250K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Re-posted 2 days ago


Job description

What's the role?

At HERE Technologies, we are transforming the future of autonomous driving by combining one of the world's richest sources of map and drive data with cutting-edge generative AI. As ADAS and Automated Driving systems increasingly rely on model-driven intelligence, we are building the next generation of AI-powered spatial intelligence platforms that create scalable, high-quality synthetic driving environments for training and validation.

We are seeking a highly experienced AI scientist and technical leader who can bridge the worlds of generative AI and autonomous vehicle simulation. In this role, you will lead the development of map-grounded world foundation models, enabling the creation of realistic, controllable, and measurable synthetic driving scenarios that accelerate the next generation of perception and planning systems.

As a Senior Principal AI Scientist, you will:

  • Lead the technical strategy and development of map-grounded world foundation models, leveraging HERE map and drive data to generate realistic and controllable driving scenarios.
  • Train, fine-tune, and deploy advanced generative AI models, including diffusion models, transformer-based world models, and generative video architectures for autonomous driving applications.
  • Drive proof-of-concept initiatives with strategic technology partners, establishing measurable success criteria and translating research outcomes into actionable business recommendations.
  • Bridge generative AI workflows with AV simulation platforms such as CARLA, NVIDIA Drive Sim, and other industry-standard environments to support training and validation use cases.
  • Define and implement quality frameworks that evaluate synthetic data utility, controllability, coverage, and downstream model performance.
  • Collaborate across machine learning, perception, planning, simulation, and product teams to ensure synthetic data solutions deliver measurable improvements in real-world autonomous driving performance.
  • Serve as a trusted technical advisor to engineering and business leaders, translating complex AI concepts into strategic opportunities and product roadmaps.
Who are you?

You are a recognized expert in both deep learning and autonomous vehicle simulation, with a proven record of turning advanced AI research into production-ready solutions. You are equally comfortable training large-scale world models, designing simulation-based validation strategies, and influencing technical direction across multidisciplinary teams.

You bring:
  • Advanced degree (M.S. or Ph.D.) in Computer Science, Artificial Intelligence, Robotics, Machine Learning, or a related field.
  • 10+ years of experience in machine learning, autonomous systems, simulation, robotics, or related disciplines, including significant hands-on experience developing and deploying AI models.
  • Deep expertise in generative AI, including diffusion models, generative video systems, transformer architectures, world models, or related foundation model technologies.
  • Strong proficiency in Python and PyTorch, with experience building scalable research and production ML pipelines.
  • Hands-on experience with autonomous vehicle simulation platforms such as CARLA, NVIDIA Drive Sim, or equivalent simulation environments.
  • Strong understanding of OpenDRIVE, OpenSCENARIO, ASAM OpenX standards, scenario-based validation, and sim-to-real methodologies.
  • Experience evaluating synthetic data quality for machine learning applications, including controllability, diversity, coverage, label fidelity, and downstream model effectiveness.
Nice to have:
  • Experience with NVIDIA Cosmos, Cosmos-Transfer, or other world foundation model platforms.
  • Background in reinforcement learning, end-to-end driving systems, or multi-agent simulation.
  • Experience in automotive, robotics, or other safety-critical domains, including familiarity with ISO 26262 and SOTIF concepts.
  • Contributions to research publications, patents, open-source AI projects, or industry-leading innovation initiatives.
  • Experience with Unreal Engine, Unity, sensor simulation, or large-scale training infrastructure.
What sets you apart:
  • You thrive at the intersection of research and execution, translating innovation into real-world impact.
  • You can communicate effectively with AI researchers, simulation engineers, product managers, and executive stakeholders.
  • You are hands-on, data-driven, and focused on measurable outcomes rather than theoretical perfection.
  • You bring a systems-thinking mindset, understanding how decisions in data generation affect downstream AI performance.
  • You are passionate about building technology that advances the future of autonomous mobility.

    The expected base salary range for this position is $170,600 to $250,000 per year. Actual compensation will be based on factors such as skills and experience. This position is also eligible for an annual performance bonus, which is subject to company and individual performance. 

    Life at HERE comes with generous benefits to support your health and overall wellness. Benefits available to US-based HERE employees include health (Medical/Dental/Vision) insurance, retirement savings plans, paid time off & leave policies.   

    As part of HERE Technologies employment process, candidates will be required to successfully complete a background verification process. Offers of employment and any related claims are subject to the successful completion of a background verification. Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, HERE will consider for employment qualified applicants with arrest and conviction records. 

    HERE is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, age, gender identity, sexual orientation, marital status, parental status, religion, sex, national origin, disability, veteran status, and other legally protected characteristics.  

    Under Section 503 of the Rehabilitation Act of 1973 and VEVRAA, we have developed an affirmative action program (AAP) for individuals with disabilities and protected veterans. Portions of the AAP are available for review by applicants and employees through our People Team. 

    #LI-SA3

Who are we?

HERE Technologies is a location data and technology platform company. We empower our customers to achieve better outcomes - from helping a city manage its infrastructure or a business optimize its assets to guiding drivers to their destination safely.

At HERE we take it upon ourselves to be the change we wish to see. We create solutions that fuel innovation, provide opportunity and foster inclusion to improve people's lives. If you are inspired by an open world and driven to create positive change, join us. Learn more about us on our YouTube Channel.

As ADAS/AD moves towards model-driven intelligence, industry value is extending from map delivery to model training and validation. HERE can convert its map and drive data into a scalable AI model-creation platform - capturing significant value from training, validation and next generation ADAS/AD performance.

It's the growth of HERE's AI-model creation platform that turns maps and drive data into reusable spatial intelligence - powering scalable training, validation, and next generation ADAS/AD performance.

Employment Type: OTHER