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Remote Computer Vision Postdoc Jobs (NOW HIRING)

Pano

Senior AI/Computer Vision Engineer

San Francisco, CA · On-site +1

$195K - $255K/yr

We are a team of more than 175 people working in a hybrid-remote environment across North America ... As a Senior AI/Computer Vision Engineer, you will lead the design, development, optimization, and ...

CACI

Staff Computer Vision AI/ML Engineer

Aurora, CO · Remote

As a CV AI/ML Engineer, you will apply cutting-edge AI/ML-based Computer Vision algorithms to problems in remote sensing, including Automatic Target Recognition (ATR) and Multimodal Data Fusion for ...

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Remote Computer Vision Postdoc information

What is a remote computer vision postdoc?

A Remote Computer Vision Postdoc is a research position for individuals who have recently completed their Ph.D. and are specializing in the field of computer vision, all while working remotely. These postdoctoral researchers typically conduct advanced studies on topics such as image recognition, object detection, and machine learning algorithms, often collaborating with academic institutions or industry labs. The remote aspect allows for flexible work locations, making it possible to join international teams and contribute to projects from anywhere in the world. This role often emphasizes publishing research, developing prototypes, and contributing to open-source projects.

What are the key skills and qualifications needed to thrive as a remote computer vision postdoc?

To thrive as a Remote Computer Vision Postdoc, you need a solid background in computer vision, machine learning, and programming, typically supported by a PhD in computer science or a related field. Proficiency with deep learning frameworks (such as TensorFlow or PyTorch), coding languages like Python or C++, and experience with large-scale data processing are essential. Strong problem-solving abilities, self-motivation, and effective remote communication skills help you excel in collaborative, research-driven environments. These competencies ensure you can independently advance research objectives, contribute innovative solutions, and work efficiently with distributed teams.

What are some common challenges faced by remote computer vision postdocs, and how can they be addressed?

Remote Computer Vision Postdocs often encounter challenges related to collaboration and access to computational resources. Since much of the work involves large datasets and high-performance computing, ensuring secure and efficient remote access to servers and data is crucial. Effective communication with mentors and team members, often across different time zones, requires proficiency with collaboration tools and proactive scheduling. To address these challenges, it can be helpful to establish regular check-ins, document workflows clearly, and leverage cloud-based platforms for data processing and code sharing.
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Remote Computer Vision Postdoc jobs near you
Infographic showing various Remote Computer Vision Postdoc job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 76% Full Time, 17% Part Time, and 6% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution.

Senior Computer Vision Engineer ID72408

Tampa, FL • On-site, Remote

AgileEngine
Software Development • 201 - 500 employees
Learn more about AgileEngineexternal

$98K - $135K/yr

Full-time

Posted 24 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;
- Upper-intermediate English level.

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.