Amazon – Associate, ML Data Operations, GO-AI Operations

Job Description

Amazon is hiring an Associate, ML Data Operations – GO-AI Operations to support its cutting-edge robotics and fulfillment technologies. This role offers an excellent opportunity for graduates who are interested in artificial intelligence operations, machine learning data annotation, image and video auditing, and operational excellence. As part of Amazon's GO-AI Operations team, you will contribute to improving automation across Amazon Robotics Fulfillment Centers by accurately reviewing videos and images that help train and enhance machine learning systems. The position requires exceptional attention to detail, analytical thinking, and the ability to make accurate judgments while handling high-volume visual data. It is an ideal role for candidates looking to begin a career in AI operations, data quality, and intelligent automation.

In this position, you will carefully review hundreds of short videos and images during each shift to verify product placement, inventory accuracy, and fulfillment center operations. Using specialized annotation tools, you will identify product locations, audit visual information, and ensure high-quality outputs that directly improve machine learning models and robotic automation systems. Accuracy and consistency are critical because every audited image contributes to Amazon's inventory management and warehouse optimization processes. The role also involves maintaining productivity targets, following operational guidelines, and adapting to rotational work schedules while collaborating with remote and onsite teams.

Joining Amazon provides an opportunity to work within one of the world's most advanced AI-powered operational environments. Associates receive exposure to machine learning workflows, computer vision technologies, robotics automation, and large-scale fulfillment operations. The experience gained in this role builds strong analytical, observational, and quality assurance skills that are highly valuable for future careers in AI Data Operations, Machine Learning, Data Annotation, Quality Assurance, Robotics Operations, Business Operations, and Technical Support. Candidates who perform consistently can further develop their careers within Amazon's rapidly expanding technology and operations ecosystem.

Roles & Responsibilities

1. Review and audit hundreds of short video clips and images during each shift to accurately identify product placement, storage activities, and fulfillment center operations.
2. Analyze visual content using specialized annotation tools while maintaining exceptional attention to detail, consistency, and data accuracy.
3. Verify product locations and inventory information to support Amazon Robotics systems in maintaining high warehouse inventory accuracy.
4. Identify details in blurry, low-quality, or partially visible videos by applying strong observation skills and sound human judgment.
5. Meet daily productivity, quality, and accuracy targets while ensuring compliance with established operational guidelines and standard operating procedures.
6. Perform image, video, and text-based annotation tasks that contribute to improving machine learning models and warehouse automation systems.
7. Collaborate effectively with supervisors and team members by participating in quality improvement initiatives, coaching sessions, and performance reviews.
8. Maintain confidentiality and data security while handling sensitive operational information and following Amazon's workplace policies.
9. Work efficiently in rotational shifts, including night shifts, weekends, and holidays, based on business requirements and operational schedules.
10. Participate in virtual meetings, operational updates, and team discussions while maintaining professionalism and adherence to organizational standards.
11. Continuously improve auditing speed and decision-making accuracy by learning new processes and incorporating performance feedback.
12. Support operational excellence by contributing to defect reduction, process optimization, and continuous quality improvement initiatives.

Requirements & Eligibility

1. Bachelor's degree in any discipline from a recognized university is mandatory for applying to this position.
2. Strong observational skills with the ability to accurately interpret image, video, and text-based information under time-sensitive conditions.
3. Excellent attention to detail and concentration while reviewing large volumes of visual data without compromising quality.
4. Ability to identify subtle visual differences and analyze unclear or low-resolution images using logical reasoning and careful judgment.
5. Good communication skills and the ability to understand instructions, collaborate with remote teams, and adapt to changing business requirements.
6. Willingness to work in rotational shifts, including night shifts, weekends, and public holidays, based on operational needs.
7. Comfortable working in a fast-paced environment while consistently meeting productivity, quality, and accuracy benchmarks.
8. Basic computer proficiency with the ability to work efficiently using web-based tools, productivity applications, and annotation platforms.
9. Ability to maintain a dedicated and distraction-free workspace when working remotely, ensuring confidentiality and operational compliance.
10. Positive attitude, adaptability, teamwork, and a willingness to learn new technologies, operational workflows, and machine learning support processes.

Expected Salary

The expected salary for the Associate, ML Data Operations – GO-AI Operations role at Amazon typically ranges between ₹2.8 LPA and ₹4.8 LPA, depending on the candidate's qualifications, location, interview performance, and prior work experience. Employees working rotational night shifts may also receive additional shift allowances and other operational benefits as per Amazon's company policies. The role provides valuable industry experience in machine learning operations, AI data annotation, and fulfillment technology, making it an excellent starting point for careers in artificial intelligence and data operations.

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