Amazon Recruitment 2025 brings an excellent opportunity for graduates and freshers who are looking to start their career with one of the world’s most trusted global technology companies. Amazon Development Center India is currently hiring for the position of Associate, ML Data Operations – GO-AI Operations as part of its ongoing off campus drive. This role is ideal for candidates interested in operations, data auditing, and supporting large-scale automation systems used in Amazon’s fulfillment centers.
This freshers hiring opportunity is a non-technical, operations-focused role that plays a critical part in maintaining inventory accuracy and improving stow quality through video and image audits. Based in Hyderabad, this position offers exposure to Amazon’s robotics and fulfillment technologies while working in a fast-paced, data-driven environment.
Amazon Recruitment 2025
| Details | Information |
|---|---|
| Company Name | Amazon |
| Job Role | Associate, ML Data Operations (GO-AI Operations) |
| Qualification | Bachelor’s Degree |
| Experience | Freshers / Entry-Level |
| Location | Hyderabad, India |
| Employment Type | Contract (6 Months) |
| Salary | Expected ₹3.5 LPA – ₹4.5 LPA |
Job Overview
The Associate, ML Data Operations role is an operational position focused on auditing short video clips and images captured inside Amazon fulfillment centers. These videos record stowing actions, and associates are responsible for carefully reviewing them to identify product placement and storage accuracy.
Associates use internal tools and guidelines to mark or verify product locations with a high degree of accuracy. The role requires strong attention to detail, consistent productivity, and the ability to work in rotational shifts in a 24×7 environment. This is a 6-month contract role, making it a suitable option for fresh graduates seeking experience with a reputed organization.
Key Responsibilities
As part of Amazon’s ML Data Operations team, associates will handle a variety of responsibilities, including:
- Reviewing hundreds of short videos or images during each shift
- Auditing stowing actions and identifying correct product locations
- Ensuring high accuracy and productivity as per defined quality metrics
- Using human judgment to interpret blurry or less sharp video footage
- Following predefined processes and acceptable practices strictly
- Maintaining consistent performance on incremental quality and productivity goals
- Working in rotational shifts, including night shifts and weekends
- Spending 6.8 to 7 hours per day actively reviewing video tasks
- Adhering to Amazon’s work-from-home or office attendance requirements when applicable
This role directly contributes to defect reduction and helps improve the efficiency of automated stowing processes.
Skills Required
To succeed in this Amazon off campus drive role, candidates should demonstrate the following skills and attributes:
- Strong attention to detail and ability to focus for extended periods
- Comfort with auditing image, video, and text-based data
- Ability to identify details in fast-moving or low-quality videos
- Willingness to work in a non-technical role for the full contract duration
- Consistent performance in a fast-paced operational environment
- Flexibility to work rotational shifts, including night shifts
- Basic computer skills and ability to use internal tools efficiently
- Good teamwork and communication skills for remote and on-site collaboration
Candidates working from home must maintain a dedicated workspace with proper lighting and ensure data confidentiality at all times.
Why Join Amazon
Joining Amazon as part of the Amazon Recruitment 2025 drive offers several benefits, especially for freshers starting their professional journey:
- Opportunity to work with a globally respected brand
- Exposure to cutting-edge automation and fulfillment technologies
- Structured training and performance coaching
- Inclusive and diverse workplace culture
- Night shift allowance as per company policy
- Fixed working hours with rotational weekly offs
- Valuable experience that strengthens future career prospects
Amazon’s inclusive culture empowers employees to perform at their best while maintaining high operational standards.
Salary Details
The salary for the Associate, ML Data Operations role is competitive and aligned with Amazon’s internal compensation structure. In addition to base pay, associates working night shifts are eligible for a night shift allowance as per Amazon’s work policy. Exact salary details will be communicated during the hiring process.
Hiring Locations
This Amazon freshers hiring opportunity is primarily based in Hyderabad, Telangana, under Amazon Development Center India. Depending on business requirements, associates may work from home or be required to report to the office for certain days.
How to Apply
Interested and eligible candidates can apply through the official Amazon Careers portal. Applicants are advised to carefully review the job description and ensure they meet the basic qualification criteria before submitting their application. Candidates requiring workplace accommodations during the hiring process can access Amazon’s accommodation support resources available on the careers website.
Amazon Apply Link : Click here
Note: Early application is recommended, as Amazon off campus drive roles tend to attract a high volume of applicants.
About the Company
Amazon is a global leader in e-commerce, cloud computing, logistics, and artificial intelligence. Through its fulfillment centers and advanced robotics systems, Amazon continues to redefine how products are stored, picked, and delivered to customers. Amazon Development Center India (ADCI) plays a crucial role in building and supporting technology and operational excellence across global Amazon facilities.
The GO-AI Operations team supports Amazon Robotics Fulfillment Centers by enabling automation through human-assisted data auditing. This team ensures that automated systems learn from accurate, high-quality human-reviewed data, helping Amazon maintain world-class inventory accuracy and operational efficiency.
