Machine Learning Task Evaluator

4 days ago


Malappuram, Kerala, India beBeeAnnotation Full time ₹ 6,00,000 - ₹ 10,00,000
Job Title: Data Annotator

About our client:

They are a leading IT services and consulting company, headquartered in Paris, France.

Founded in 1967, they have been at the forefront of business transformation for over 50 years, leveraging technology to address a wide range of business needs.

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

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

Key Responsibilities:

  • Watch short robotic task videos and 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.
  • Two years of experience or more with technical background in any programming language.

Benefits:

  • A consistent flow of engaging projects
  • The opportunity to work with cutting-edge technologies
  • The satisfaction of contributing to high-quality training data

What Success Looks Like:

  • Delivering accurate and consistent annotations
  • 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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