... video datasets. You will curate and manage annotation workflows, run model training and evaluation jobs, maintain benchmarks, and collaborate with senior engineers on failure-case analysis. The role ...
... video datasets. You will curate and manage annotation workflows, run model training and evaluation jobs, maintain benchmarks, and collaborate with senior engineers on failure-case analysis. The role ...
... video datasets. You will curate and manage annotation workflows, run model training and evaluation jobs, maintain benchmarks, and collaborate with senior engineers on failure-case analysis. The role ...
... video datasets. You will curate and manage annotation workflows, run model training and evaluation jobs, maintain benchmarks, and collaborate with senior engineers on failure-case analysis. The role ...
... video datasets. You will curate and manage annotation workflows, run model training and evaluation jobs, maintain benchmarks, and collaborate with senior engineers on failure-case analysis. The role ...
... video datasets. You will curate and manage annotation workflows, run model training and evaluation jobs, maintain benchmarks, and collaborate with senior engineers on failure-case analysis. The role ...
... video datasets. You will curate and manage annotation workflows, run model training and evaluation jobs, maintain benchmarks, and collaborate with senior engineers on failure-case analysis. The role ...
... video datasets. You will curate and manage annotation workflows, run model training and evaluation jobs, maintain benchmarks, and collaborate with senior engineers on failure-case analysis. The role ...
... video datasets. You will curate and manage annotation workflows, run model training and evaluation jobs, maintain benchmarks, and collaborate with senior engineers on failure-case analysis. The role ...
... video datasets. You will curate and manage annotation workflows, run model training and evaluation jobs, maintain benchmarks, and collaborate with senior engineers on failure-case analysis. The role ...
... video datasets. You will curate and manage annotation workflows, run model training and evaluation jobs, maintain benchmarks, and collaborate with senior engineers on failure-case analysis. The role ...
... video datasets. You will curate and manage annotation workflows, run model training and evaluation jobs, maintain benchmarks, and collaborate with senior engineers on failure-case analysis. The role ...
... video datasets. You will curate and manage annotation workflows, run model training and evaluation jobs, maintain benchmarks, and collaborate with senior engineers on failure-case analysis. The role ...
... video datasets. You will curate and manage annotation workflows, run model training and evaluation jobs, maintain benchmarks, and collaborate with senior engineers on failure-case analysis. The role ...
Senior Video Annotation information
What is a senior video annotation?
A Senior Video Annotation specialist is a professional responsible for labeling, tagging, and categorizing objects or actions within video data, often for use in machine learning and artificial intelligence projects. They oversee and guide annotation teams, ensure high-quality data labeling, and help develop guidelines and best practices. Their expertise is crucial for training accurate computer vision models, as they provide the ground truth data that algorithms learn from.
What are the key skills and qualifications needed to thrive as a senior video annotation specialist, and why are they important?
To excel as a Senior Video Annotation Specialist, you need advanced skills in data labeling, attention to detail, and experience with video annotation tools, often supported by a degree in computer science or a related field. Familiarity with annotation platforms like CVAT, Labelbox, or VGG Image Annotator, and understanding of basic machine learning concepts, are typically required. Strong organizational skills, problem-solving abilities, and effective communication help ensure accuracy and seamless collaboration with data science teams. These competencies are vital for producing high-quality annotated datasets that drive the performance of computer vision models.
What are some common challenges faced by senior video annotation professionals, and how can they be addressed?
Senior Video Annotation professionals often encounter challenges such as maintaining consistency in labeling complex visual data, meeting tight project deadlines, and managing large volumes of video content. To address these issues, it's important to establish clear annotation guidelines, utilize efficient annotation tools, and foster open communication within the annotation team. Regular training and quality assurance checks can also help ensure high accuracy and efficiency, positioning team members for leadership and quality control roles as they advance.
What is the difference between Senior Video Annotation vs Video Labeler?
| Aspect | Senior Video Annotation | Video Labeler |
|---|---|---|
| Required Credentials | Typically requires experience in annotation tools, basic understanding of video content, and sometimes a degree in related fields | Usually requires familiarity with labeling software and basic video content understanding, but less experience needed |
| Work Environment | Often part of a team working on complex projects, possibly remote or in-office | Typically focused on individual tasks, often remote, with repetitive labeling work |
| Employer & Industry Usage | Used in AI/ML companies, autonomous vehicle development, and tech firms | Common in data annotation companies, AI startups, and research labs |
Senior Video Annotation roles involve more complex tasks, oversight, and experience, while Video Labelers focus on basic labeling tasks. The senior role often requires a deeper understanding of video content and annotation tools, making it suitable for those with more experience. Both roles are essential in AI data preparation but differ in scope and responsibility.
What are the most commonly searched types of Video Annotation jobs in Florida?
The most popular types of Video Annotation jobs in Florida are:
What are popular job titles related to Senior Video Annotation jobs in Florida?
For Senior Video Annotation jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Senior Video Annotation jobs in Florida look for?
The top searched job categories for Senior Video Annotation jobs in Florida are:
What cities in Florida are hiring for Senior Video Annotation jobs?
Cities in Florida with the most Senior Video Annotation job openings:
Junior/Middle Computer Vision Engineer ID72410
Orlando, FL • On-site
AgileEngine •
Software Development • 201 - 500 employees201 - 500 employees
Full-time
Posted 7 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 Junior/Middle Computer Vision Engineer to support high-volume execution across data preparation, model training, and evaluation for an AI team working with large-scale image and video datasets. You will curate and manage annotation workflows, run model training and evaluation jobs, maintain benchmarks, and collaborate with senior engineers on failure-case analysis. The role offers a a clear growth path into applied modeling or MLOps for an early-career engineer eager to build hands-on AI experience.
WHAT YOU WILL DO
- Curate large-scale image and video datasets, manage labeling processes and workflows, and ensure the highest standards for dataset quality;
- Run model training and evaluation jobs, ensuring experiments are executed smoothly and efficiently;
- Document training results, maintain ongoing evaluation benchmarks, and track model performance over time;
- Collaborate with senior engineers to analyze model failure cases and identify areas for data or algorithmic improvement;
- Take ownership of foundational tasks that support the broader team's AI/ML lifecycle, directly contributing to the speed and success of production deployments.
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;
- 1 to 3 years of experience in software engineering, data science, machine learning, or a related field;
- Degree in Computer Science, Data Science, Engineering, 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);
- Foundational coding skills in Python;
- Foundational understanding of machine learning concepts and workflows;
- Basic knowledge of computer vision principles (e.g., image processing, object detection basics);
- Basic familiarity with cloud environments and compute resources;
- A strong, demonstrable willingness to learn and adapt in a fast-paced, mentorship-driven environment;
- Excellent attention to detail, specifically regarding data quality and documentation;
- 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.
About AgileEngine
Sourced by ZipRecruiter
Industry
Software development
Company size
201 - 500 Employees
Headquarters location
McLean, VA, US
Year founded
2000