You will curate and manage annotation workflows, run model training and evaluation jobs, maintain ... WHAT YOU WILL DO - Curate large-scale image and video datasets, manage labeling processes and ...
You will curate and manage annotation workflows, run model training and evaluation jobs, maintain ... WHAT YOU WILL DO - Curate large-scale image and video datasets, manage labeling processes and ...
You will curate and manage annotation workflows, run model training and evaluation jobs, maintain ... WHAT YOU WILL DO - Curate large-scale image and video datasets, manage labeling processes and ...
You will curate and manage annotation workflows, run model training and evaluation jobs, maintain ... WHAT YOU WILL DO - Curate large-scale image and video datasets, manage labeling processes and ...
You will curate and manage annotation workflows, run model training and evaluation jobs, maintain ... WHAT YOU WILL DO - Curate large-scale image and video datasets, manage labeling processes and ...
You will curate and manage annotation workflows, run model training and evaluation jobs, maintain ... WHAT YOU WILL DO - Curate large-scale image and video datasets, manage labeling processes and ...
Expertise in data annotation and labelling technologies with ability to institute and maintain the program. * Experience with NVIDIA Omniverse, including USD workflows, Omniverse Kit/Code, PhysX, or ...
Expertise in data annotation and labelling technologies with ability to institute and maintain the program. * Experience with NVIDIA Omniverse, including USD workflows, Omniverse Kit/Code, PhysX, or ...
Expertise in data annotation and labelling technologies with ability to institute and maintain the program. * Experience with NVIDIA Omniverse, including USD workflows, Omniverse Kit/Code, PhysX, or ...
Expertise in data annotation and labelling technologies with ability to institute and maintain the program. * Experience with NVIDIA Omniverse, including USD workflows, Omniverse Kit/Code, PhysX, or ...
Annotation Labelling information
What is annotation labelling?
Annotation labelling is the process of tagging or marking data—such as images, text, or audio—with relevant information or labels. This is an essential step in preparing datasets for machine learning and artificial intelligence models, as it helps algorithms understand and learn from raw data. Annotation labelling can include tasks like identifying objects in photos, transcribing speech, or categorizing text. Skilled annotators ensure accuracy and consistency to improve model performance. People in this role often use specialized tools or software to streamline and standardize the annotation process.
What are the key skills and qualifications needed to thrive as an annotation labelling specialist?
To thrive as an Annotation Labelling Specialist, you need strong attention to detail, data analysis capabilities, and familiarity with data annotation standards, usually supported by a background in computer science or related fields. Proficiency with annotation tools such as Labelbox, CVAT, or Supervisely, and sometimes knowledge of basic programming or scripting, is typically required. Excellent communication, consistency, and the ability to follow complex instructions are crucial soft skills for producing high-quality labeled data. These skills ensure the accuracy and reliability of datasets, which are foundational for successful machine learning and AI model development.
What are some common challenges faced by annotation labelling professionals, and how can they be managed?
Annotation Labelling professionals often encounter challenges such as maintaining high accuracy while handling repetitive data, meeting tight deadlines, and adapting to evolving project guidelines. To manage these, it’s important to develop strong attention to detail, regularly communicate with team leads to clarify instructions, and leverage annotation tools efficiently. Collaborating closely with quality assurance teams can also help identify and correct errors early, ensuring consistently high-quality outputs.
What is the difference between Annotation Labelling vs Data Labeling Specialist?
| Aspect | Annotation Labelling | Data Labeling Specialist |
|---|---|---|
| Credentials | Basic technical skills, attention to detail | Similar skills, sometimes additional domain knowledge |
| Work Environment | Data annotation platforms, remote or office | Data annotation tasks, often remote or in-office |
| Industry Usage | AI, machine learning, autonomous vehicles | AI, machine learning, healthcare, retail |
| Search & Comparison | Commonly compared for entry-level data tasks | Related but broader role |
Annotation Labelling involves marking data such as images, text, or videos to train AI models. Data Labeling Specialists perform similar tasks but may have a broader scope, including verifying and managing labeled data. Both roles are essential in AI development, often overlapping in skills and work environment, but Annotation Labelling is more focused on the annotation process itself.
What are popular job titles related to Annotation Labelling jobs in Fort Worth, TX? For Annotation Labelling jobs in Fort Worth, TX, the most frequently searched job titles are:
What job categories do people searching Annotation Labelling jobs in Fort Worth, TX look for? The top searched job categories for Annotation Labelling jobs in Fort Worth, TX are:
What cities near Fort Worth, TX are hiring for Annotation Labelling jobs? Cities near Fort Worth, TX with the most Annotation Labelling job openings:
Full-time
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 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