2

Remote Video Labelling Jobs in Oregon (NOW HIRING)

... onsite, remote or hybrid) environment, including consistent use of video conferencing ... Monroney Labels, and Interact RV. We are an international company with offices located in the ...

New

... onsite, remote or hybrid) environment, including consistent use of video conferencing ... Monroney Labels, and Interact RV. We are an international company with offices located in the ...

New

... remote, or hybrid), including consistent use of video conferencing, collaboration tools, and ... Labels and Interact RV. Each one is an industry leader in driving consumer engagement and ...

New

... remote, or hybrid), including consistent use of video conferencing, collaboration tools, and ... Labels and Interact RV. Each one is an industry leader in driving consumer engagement and ...

... onsite, remote or hybrid) environment, including consistent use of video conferencing ... Monroney Labels, and Interact RV. We are an international company with offices located in the ...

New

Senior Product Manager

$126K - $166K/yr

... onsite, remote or hybrid) environment, including consistent use of video conferencing ... Monroney Labels, and Interact RV. We are an international company with offices located in the ...

... onsite, remote or hybrid) environment, including consistent use of video conferencing ... Monroney Labels, and Interact RV. We are an international company with offices located in the ...

New

Remote Video Labelling information

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 Oregon? The most popular types of Video Labelling jobs in Oregon are:
What job categories do people searching Remote Video Labelling jobs in Oregon look for? The top searched job categories for Remote Video Labelling jobs in Oregon are:
What cities in Oregon are hiring for Remote Video Labelling jobs? Cities in Oregon with the most Remote Video Labelling job openings:
Senior Machine Learning Engineer, Computer Vision

Senior Machine Learning Engineer, Computer Vision

Overwatch Imaging

Hood River, OR โ€ข On-site, Remote

$128K - $168K/yr

Full-time

Medical, Dental, Retirement, PTO

Posted 18 days ago


Job description

About Overwatch:

Overwatch Imaging is an imagery intelligence technology company working to bring sensor autonomy to time-critical airborne search, detection,trackingand monitoring missions. Our Automated Sensor Operator (ASO) software, native to our own line of purpose-built Smart Sensors and as an upgrade for airborne video gimbal platforms, bringsSuperhuman VisionandWorkload Reductionto users of real-time imagery intelligence systems. We fundamentally believe that modern edge processing and AI-enabled autonomy can perform an important set of time-critical imagery intelligence missions better,fasterand moresafely than humans can alone.

Founded in 2016 in Hood River, Oregon, we support private sector companies as well as federal,stateand local agencies around the world with missions ranging from wildfire mapping and disaster response to law enforcement, border security, maritime domainawarenessand tactical intelligence.

About this Role:

Join our dynamic team to build, maintain, and optimize the end-to-end data and model pipelines that power our core Artificial Intelligence systems. This is a hands-on role perfect for an ambitious engineer who is passionate about taking raw data through the entire lifecycle, from scraping and wrangling to production-ready, trained models.
This role is remote-friendly, with a preference for candidates who can spend occasional time onsite in Hood River, OR.

What You'll Do:

  • MLOps and Training Infrastructure
    • Design and improve training pipelines to support faster, continuous model iteration
    • Enable scalable experimentation across datasets, model architectures, and training strategies
    • Improve reproducibility, experiment tracking, and comparison of training runs
  • Data Pipelines and Dataset Quality
    • Build and refine workflows for:
      • Data indexing, curation, and preprocessing
      • Label quality validation and dataset management
      • Data exploration for targeted labeling
    • Develop evaluation and tests that reflect real-world operating conditions
    • Improve synthetic data workflows to support targeted model improvement
  • Model Development and Experimentation
    • Train, evaluate, and iterate on computer vision models for:
      • Detection, segmentation, classification, tracking
      • Transformer and multi-modal architectures where appropriate
    • Continuously explore and evaluate:
      • new model families and research directions
      • Domain-specific optimizations for aerial imagery, small-object detection
    • Incorporate multi-modal inputs including:
      • Multiple image bands
      • Platform and sensor metadata (range, angles, telemetry, etc.)
  • Edge deployment and Optimization
    • Optimize models for deployment on embedded GPU platforms like Nvidia Jetson
    • Balance accuracy, latency, and resource constraints for real-world, real-time workflows


What You'll Bring

Core Experience

  • 5+ years of experience in machine learning, with a focus on computer vision
  • B.S., M.S., or Ph.D. in Computer Science, Engineering, or a related technical field, or equivalent practical experience
  • Hands-on experience building and improving computer vision or perception modelsinproduction or real-world systems, especiallyfor object detection, object tracking
  • Strong understanding of model evaluation, including selecting metrics, building test sets, analyzing false positives/false negatives, and measuring performance over timefor iterative improvement


Technical Skills

  • Experience with PyTorch or Tensorflow
  • Strong understanding of modern computer vision architectures:
    • CNNs, transformers (ViTs), and/or multi-model models
    • OpenCV, NumPy, or similar
  • Experience building training and data pipelines for medium to large scale datasets
  • Strong python skills and solid software engineering fundamentals


Bonus

  • Aerial imagery, geospatial data, or remote sensing
  • Photogrammetry
  • Multi-modal learning systems
  • Familiarity with state estimation and tracking methods (Kalman Filters, DeepSORT, ByteTrack, etc)
  • Experience with performance languages (C++or similar)
  • Model deployment onto Nvidia Jetson based edge hardware


What We Offer:

  • Growth Opportunities: As a team member of a true startup, you will learn by doing and shape our future. The opportunities are limitless for those who want to grow their career.
  • Impact Opportunity: We work on missions that matter to keep people safe and make the world better, and we do it without bureaucracy at the speed of a startup.
  • Team Collaboration: Work in a fast-paced, collaborative environment with amazing teammates. The Overwatch Imaging leadership team believes in an open-door policy, meaning everyone has a voice and access to guidance, advice, feedback, and the ability to pitch crazy new products or ideas.
  • Late Start Wednesday: A weekly block to have focus time away from meetings and calls. An opportunity to work from home, flex your schedule or self-directed time to focus on training and development.
  • Time Off: Generous PTO to empower employees to make decisions about work life balance based on work and home needs.
  • Holidays: Overwatch Imaging recognizes 10 company holidays.
  • Ownership: Equity/Stock Options in our rapidly growing company.
  • Health Benefits: Medical/Dental premiums 100% covered by Overwatch Imaging for employees and their families, plus available pre-tax health savings account.
  • 401K: Employer matching contributions up to 4% of pay.

All applicants must be authorized to work on a permanent basis in the United States.

Overwatch Imaging is an equal opportunity workplace and makes employment decisions based on merit and business needs, regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity, Veteran status, or any other protected personal characteristic.

All applicants mustbe authorized towork on a permanent basis in the UnitedStates.

Overwatch Imaging is an equal opportunity workplace and makes employment decisions based on merit and business needs, regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity, Veteran status, or any other protected personal characteristic.

We encourage all qualified candidates to apply, even if theydon'tmeet every requirement listed

in this job description. We value diversity of experience and perspectives and are always looking

for talented individuals to join our team.

Export Control Compliance Notice
This position may involve access to data, technology, or software that is subject to U.S. export control laws and regulations, including the International Traffic in Arms Regulations (ITAR) and/or the Export Administration Regulations (EAR). As such, employment is contingent upon the applicant's ability to obtain any necessary export authorization, asdeterminedby an export compliance assessment conducted by the company.