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Computer Vision Object Detection Jobs (NOW HIRING)

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Computer Vision Expert

$80 - $110/hr

Object Detection * Image Segmentation * Object Recognition * Vision-Language & Multimodal Reasoning ... Deep hands-on experience in Computer Vision through industry, research, or graduate/PhD-level work.

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Computer Vision Object Detection information

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How much do computer vision object detection jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for computer vision object detection in the United States is $53.11, according to ZipRecruiter salary data. Most workers in this role earn between $41.11 and $68.51 per hour, depending on experience, location, and employer.

What is computer vision object detection?

Computer Vision Object Detection is a field within artificial intelligence and computer science that focuses on enabling computers to identify and locate objects within digital images or videos. Using advanced algorithms and deep learning models, object detection systems can recognize multiple objects, determine their positions, and classify them into predefined categories. Applications of object detection include autonomous vehicles, surveillance systems, medical imaging, and retail analytics. Its effectiveness depends on the quality and diversity of the training data, as well as the complexity of the algorithms used.

How does a computer vision object detection specialist typically collaborate with software engineers and data scientists on projects?

In most organizations, Computer Vision Object Detection specialists work closely with software engineers and data scientists to integrate detection models into larger applications. They often collaborate on data collection and annotation, model training and tuning, and deploying solutions at scale. Regular cross-functional meetings and code reviews are common, ensuring that models meet performance requirements and align with broader product goals. Effective communication and teamwork are essential, as the role often involves translating technical model outputs into actionable insights for various stakeholders.

What are the key skills and qualifications needed to thrive as a computer vision object detection specialist, and why are they important?

To thrive in Computer Vision Object Detection, you need strong programming skills (especially in Python), a solid background in machine learning and deep learning, and typically a degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and OpenCV, as well as experience using annotation tools and cloud platforms, is crucial. Strong problem-solving ability, attention to detail, and effective communication skills help you design robust models and collaborate with multidisciplinary teams. These skills are essential for developing accurate and efficient object detection systems that address real-world challenges in industries like automotive, healthcare, and security.

What other helpful pages are available for Computer Vision Object Detection?

Other pages related to Computer Vision Object Detection:

Infographic showing various Computer Vision Object Detection job openings in the United States as of September 2026, with employment types broken down into 71% Full Time, and 29% Contract. Highlights an 100% In-person job distribution, with an average salary of $110,464 per year, or $53.1 per hour.

Senior Computer Vision Engineer ID72408

Tallahassee, FL • On-site

AgileEngine, LLC.
Software Development • 201 - 500 employees
Learn more about AgileEngine, LLC.external

$90K - $124K/yr

Other

Posted 18 days ago

Job description

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

WHY JOIN US

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

ABOUT THE ROLE

We are looking for a Senior Computer Vision Engineer to own applied model development across computer vision, machine learning, and data science use cases — building and deploying solutions for object detection, image segmentation, classification, and video analysis. You will evaluate and fine-tune model architectures using PyTorch and TensorFlow, build broader ML models for forecasting and anomaly detection, and apply practical knowledge of computer vision hardware including cameras, sensors, and edge devices.

WHAT YOU WILL DO
  • Own the applied model development process across computer vision, AI/ML, and broader data science use cases;
  • Translate complex business problems into viable, practical, and scalable AI/ML solutions;
  • Evaluate various model options, train and fine-tune selected architectures, and rigorously analyze model performance;
  • Develop and deploy solutions for object detection, image segmentation, image classification, and video analysis;
  • Build and maintain models for time-series forecasting, anomaly detection, regression, clustering, and general data analysis;
  • Apply practical knowledge of real-world constraints—such as lighting, sensor limitations, and edge device compute power to ensure optimal data quality and robust model performance in production.
MUST HAVES
  • You must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time;
  • 3 to 5 years of professional experience in Computer Vision, Machine Learning, Data Science, or a related field;
  • Degree in Computer Science, Engineering, Data Science, Mathematics, or a related discipline (or equivalent practical experience);
  • Engineers located in the US must reside in Dallas, TX, and be open to working from the office (onsite);
  • Strong, production-level proficiency in Python;
  • Deep hands-on experience with PyTorch and/or TensorFlow;
  • Proven track record of building and deploying models for detection, segmentation, classification, and image/video analysis;
  • Solid understanding of broader ML and data science techniques (time-series modeling, forecasting, anomaly detection, regression, and clustering);
  • Practical experience working with computer vision hardware, including cameras, sensors, and lighting setups;
  • Familiarity with deploying models on edge devices;
  • Strong understanding of how physical and real-world constraints impact data quality, model training, and inference;
PERKS AND BENEFITS
  • Professional growth: Mentorship, TechTalks, and personalized growth roadmaps.
  • Competitive compensation: USD-based pay with education, fitness, and team activity budgets.
  • Exciting projects: Modern solutions with Fortune 500 and top product companies.
  • Flextime: Flexible schedule with remote and office options.
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