Video Annotation Specialist

Job description

Job Title: Video Annotation Specialist

Location -Hyderabad

Duration - 6 months

Job Description

We are seeking a highly skilled and detail-oriented Video Annotation Specialist to contribute to a project focused on facial recognition and analysis. This role involves the meticulous annotation of video data, specifically through the identification and tracking of facial landmarks using key points across every frame of a video sequence.

The annotations you produce will be pivotal in developing and refining state-of-the-art machine learning models that can accurately interpret and analyze facial movements, expressions, and identities. You will play a critical role in ensuring that the data feeding these models is of the highest quality, enabling breakthroughs in facial recognition technology that have applications ranging from security to augmented reality and beyond. This position requires a combination of technical proficiency, attention to detail, and a deep understanding of facial structure and movement.

Key Responsibilities:

• Precise Annotation of Facial Landmarks:
• Annotate video frames by meticulously placing key points on specific facial landmarks, including but not limited to eyes, nose, mouth, eyebrows, and chin.
• Track these landmarks consistently across all frames in a video, ensuring smooth and accurate transitions to facilitate effective model training.
• Utilization of Specialized Annotation Tools:
• Work with industry-standard annotation software, leveraging its full capabilities to perform detailed key-point tracking.
• Collaboration with Cross-Functional Teams:
• Participate in team meetings to discuss challenges, share insights, and contribute to the continuous improvement of the annotation process.
• Analytical Skills:
• Ability to analyze facial movements and apply this understanding to data annotation.

Educational qualification:

• Graduation in any domain. (preference will be given to STEM fields - science, technology, engineering, and mathematics)

Experience:

• A minimum of two years of experience in video annotation, with a strong focus on face landmark tracking.

Technical Skills:

• Familiarity with video formats, frame rates, and resolution issues.
• Understanding of facial anatomy and expressions is a plus.
• Familiarity with landmark and keypoint detection in videos, understanding how these annotations are used in machine learning models.
• Understanding how annotated data is used in machine learning pipelines, particularly in training models for tasks like facial recognition, human pose estimation, or object tracking.

Interested candidates can share their resumes on rishabh@innodata.com or can call or WhatsApp on 9870131979