Associate ML Data Operations @ Amazon
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Job Details
Overview
The Associate ML Data Operations role at Amazon enables automation in Amazon Robotics Fulfillment centers. In this position, you will support Amazon Internal Fulfillment Technologies & Robotics teams by conducting real-time and offline audits (image/video) to ensure inventory accuracy and stow quality.
Key Responsibilities
As an Associate ML Data Operations, you are expected to:
- Watch and review several hundred short video clips per shift.
- Utilize human judgment with provided tools to audit stowing activity accurately.
- Mark product locations and verify details in videos/images.
- Maintain a high level of quality and productivity.
- Adhere to scheduled breaks and work shift requirements.
Job Environment & Shifts
Associates work in a 24x7 environment with rotational shifts including potential night shifts and variable shift timings. The role requires working a 9-hour shift (including breaks) and may include remote and office attendance when required.
Candidate Requirements
Candidates must demonstrate:
- A willingness to work in a non-tech, operational role for a 6-month contract.
- Exceptional attention to detail and focus during audits.
- Ability to work with image, video, and text based data in a fast-paced environment.
- Flexibility to work rotational shifts including nights, weekends, and holidays.
- Readiness to work both remotely (with a dedicated workspace) and in-office when necessary.
About the Team
The Data Auditing Operations team assists fulfillment centers by providing human oversight to enhance automated processes. Your audits help improve the accuracy of stowing activities, influencing performance improvements and coaching.
Key Skills/Competency
- Automation
- Video Auditing
- Data Review
- Quality Assurance
- Attention to Detail
- Operational Efficiency
- Shift Work
- Remote Work
- Team Collaboration
- Adaptability
How to Get Hired at Amazon
🎯 Tips for Getting Hired
- Research Amazon's culture: Understand their operational and robotics initiatives.
- Customize your resume: Highlight attention to detail and audit experience.
- Emphasize flexibility: Focus on shift work and remote readiness.
- Prepare for technical review: Be ready to discuss data auditing examples.