
Amazon is hiring for the position of Associate, ML Data Operations at its GO-AI Operations unit in Hyderabad. This 6-month contract role is perfect for detail-oriented individuals looking to contribute to automation in Amazonβs Robotics Fulfillment Centers.
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π’ Company: Amazon
π Location: Hyderabad, India
π Work Type: Full-Time (6-month contract)
πΌ Job Role: Associate β ML Data Operations
π Job ID: 2946951
ποΈ Posted On: [Insert Todayβs Date]
π Job Overview
As an Associate, you will audit hundreds of short video clips from fulfillment centers to validate inventory accuracy. Your judgment directly impacts automation systems and stow quality at Amazon Robotics Fulfillment Centers.
π Key Responsibilities
- Review and analyze hundreds of short videos daily.
- Accurately mark or verify product locations in video clips.
- Maintain high levels of accuracy and productivity.
- Collaborate in remote and rotational team environments.
- Work in rotational shifts, including nights and weekends.
- Participate in virtual meetings (camera on) and occasionally report to office if required.
π Eligibility Criteria
Basic Qualifications:
- Bachelorβs degree from a recognized institution.
- Willingness to work on a 6-month contractual role.
- High attention to detail and ability to focus on blurred or unclear video content.
Preferred Qualifications:
- Comfortable working rotational shifts (24×7), weekends, and holidays.
- Experience or capability to meet quality and productivity metrics.
- Ability to work independently and within teams.
π§βπ» Remote Work Setup Requirements
- Dedicated workspace with table, chair, and sufficient lighting.
- No unauthorized access to work data.
- Webcam access during virtual meetings is mandatory.
π Work Schedule
- Shift Duration: 9-hour shifts with pre-scheduled breaks.
- Weekly Offs: Rotational two-day consecutive offs.
- Night Shift Allowance: Provided as per company policy.
π§ About the GO-AI Operations Team
The GO-AI (Global Operations β Artificial Intelligence) team at Amazon enables automation in fulfillment centers by performing visual audits on short-duration video clips. This human-in-the-loop approach improves stow accuracy and supports seamless robotic operations.
π How to Apply:
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