Data Annotator

2 days ago

Ajmer, Rajasthan, India People Prime Worldwide Full time

About Company:-

Our client is a French multinational information technology (IT) services and consulting company, headquartered in Paris, France. Founded in 1967, It has been a leader in business transformation for over 50 years, leveraging technology to address a wide range of business needs, from strategy and design to managing operations.

The company is committed to unleashing human energy through technology for an inclusive and sustainable future, helping organizations accelerate their transition to a digital and sustainable world.

They provide a variety of services, including consulting, technology, professional, and outsourcing services.

Job Title: Data Annotator

Location: Pan India

Client: Turing

Experience: 5+ yrs.

Job Type : Contract to hire.

Notice Period:- Immediate joiners.

Job Description:-

What does day-to-day look like:

  • Watch short robotic task videos in full before annotating.
  • Identify the main objective of the robot's task as well as the smaller steps it takes.
  • Summarize what happened in the video, noting whether the task succeeded, partially succeeded, or failed, and highlight any errors or inefficiencies.
  • Provide timestamped annotations that describe, in detail, each robot movement in the video.
  • Ensure annotations adhere strictly to structured guidelines to maintain consistency across datasets.
  • Review and refine annotations based on feedback to improve accuracy and clarity.

Requirements:

  • Strong attention to detail and ability to follow structured guidelines.
  • Clear written communication skills in English.
  • Comfort with repetitive, precision-focused work.
  • Ability to differentiate between successful, partial, and failed task execution.
  • Prior experience in data annotation, transcription, or quality assurance is a plus but not required.
  • 2 years of experience or more with technical background in any programming language

What success looks like:

  • Delivering consistent, accurate annotations across tasks.
  • Capturing both the "what" (intent and actions) and the "how" (quality of execution) of robot tasks.
  • Contributing to a gold-standard dataset that supports robotics and AI training.

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