Job description
- Performs annotation for image and video files to support ground truth data generation
- Understands and follows the SOP, procedures and guidelines to execute daily tasks
- Performs repetitive annotation activities and adopts to dynamic instructions without compromising on quality
- Uses internal tools and software provided by team to track daily status completion and queries.
- May participate in data collection activities when scripts and instructions are provided.
- Adheres to compliance and confidentiality requirements.
- Meets daily productivity and quality targets.
- Suggests improvements to tools, processes, and SOPs.
A day in the life
- Performs annotation for image and video files to support ground truth data generation
- Understands and follows the SOP, procedures and guidelines to execute daily tasks
- Performs repetitive annotation activities and adopts to dynamic instructions without compromising on quality
- Uses internal tools and software provided by team to track daily status completion and queries.
- May participate in data collection activities when scripts and instructions are provided.
- Adheres to compliance and confidentiality requirements.
- Meets daily productivity and quality targets.
- Suggests improvements to tools, processes, and SOPs.
Basic qualifications
- A graduate in any field of study. Quantitative fields such as science and engineering preferred but not mandatory
- Excellent English communication and interpersonal skills.
- Good familiarity with the Windows desktop environment and use of Word, Excel, IE, Firefox etc. are required
- Basic knowledge on ML data labeling process, related tools and software used for ground truth generation.
- Flexibility and Interest to do repetitive tasks is required
- Exceptional attention to detail.
- High level of energy and proactive nature. A sense of ownership and drive and a willingness to accept the challenge of daily deadlines is essential
- Minimum of 6 months of work experience in data labeling on image/video with multiple classes of objects and attributes.
Basic qualifications
- Practical knowledge of data processing needs and trade-offs
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