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COMPANY	:	[ AMAZON ]
ROLE	:	[ Associate ]
VACANCY	:	[ 20+ ]
QUALIFICATION	:	[ BE /ME /BTECH /MTECH /DIPLOMA/ MBA /BSC /MSC /BA /MA Or Engineering Related Field ]
EXPERIENCE	:	[ Freshers ]
SALARY	:	[ Upto Rs 2,40,000 to Rs 6,20,000 / Year ]
LOCATION	:	[ Hydrabad ]

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ABOUT COMPANY :

When Amazon.com launched in 1995, it was with the mission “to be Earth’s most customer-centric company.” What does this mean? It's simple. We're a company that obsesses over our customers. Our actions, goals, projects, programs and inventions begin and end with the customer top of mind. In other words, we start with the customer and work backwards. When we hit on something that is really working for customers, we double-down on it with hopes to turn it into an even bigger success. However, it’s not always as clean as that. Inventing is messy, and over time, it’s certain that we’ll fail at some big bets too.

             

JOB DESCRIPTION :

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Required Qualifications & Skills:-

• A graduate in any field of study. Quantitative fields such as science and engineering preferred but not mandatory
• Practical knowledge of data processing needs and trade-offs
• DoExcellent 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.

Job Description & Responsibilities:-

• 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.

JOB DESCRIPTION : ( SAME DESCRIPTION ONLY USE TO PRINT OUT PERSON )

Required Qualifications & Skills:-

• A graduate in any field of study. Quantitative fields such as science and engineering preferred but not mandatory
• Practical knowledge of data processing needs and trade-offs
• DoExcellent 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.

Job Description & Responsibilities:-

• 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.

How to apply :

Click on the below link, it will take you to the source page, where you can apply

Note :

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