Job Title : Data Annotator (AI/ML)
Company: Worldwide Technology Solutions (WTS)
Location: Hyderabad (Work from Office)
Experience: 3–4 Years
Employment Type: Full-time
Notice Period: Immediate Joiners Preferred
Job Summary
Worldwide Technology Solutions (WTS) is hiring an experienced Data Annotator to support AI and Machine Learning projects. The ideal candidate should have practical experience in annotating image, video, text, audio, and multimodal datasets while ensuring high-quality annotations for AI model training.
Key Responsibilities
- Perform annotation of image, video, text, audio, and multimodal datasets.
- Execute Bounding Box, Polygon, Semantic Segmentation, Instance Segmentation, Keypoint, OCR, NER, Object Detection, Text Classification, and Object Tracking tasks.
- Review and validate annotated data to maintain quality standards.
- Follow annotation guidelines and ensure consistency across datasets.
- Collaborate with AI Engineers, ML Engineers, QA teams, and Project Managers.
- Meet project deadlines, productivity goals, and SLA requirements.
- Report annotation issues and recommend process improvements.
Required Skills
- 3–4 years of experience in AI/ML Data Annotation.
- Strong knowledge of Computer Vision and NLP annotation techniques.
- Hands-on experience with CVAT, Label Studio, Labelbox, Supervisely, Doccano, V7 Darwin, or similar annotation platforms.
- Understanding of annotation formats such as COCO, YOLO, Pascal VOC, JSON, XML, and CSV.
- Experience in dataset validation, quality assurance, and error analysis.
- Basic knowledge of AI/ML workflows and data preparation.
- Strong analytical skills and attention to detail.
- Excellent communication and teamwork skills.
Preferred Qualification
- Bachelor's degree in Computer Science, IT, Engineering, Data Science, or a related field.
- Experience working on Computer Vision, NLP, Speech AI, or Generative AI projects is an added advantage.
Interested candidates may send their updated resume to:
[email protected]
Pay: From ₹400,000.00 per year
Work Location: In person
