Associate, ML Data Operations, GO-AI Operations

Amazon's interview process usually consists of an initial online assessment or screening, followed by one or two virtual functional interviews focused on role‑specific scenarios and data‑handling abilities. The final HR round evaluates cultural fit and discusses compensation. The difficulty is moderate; preparation should focus on Amazon's leadership principles, situational judgment, and basic data annotation concepts.

Amazon fosters a fast‑paced, data‑centric culture where employees are encouraged to think big and own their projects. The company offers clear career ladders, regular feedback loops, and a strong emphasis on learning and development. While the workload can be intense, Amazon provides flexible shift options and a supportive environment for remote workers.

Bachelor's degree in any discipline; must have a stable internet connection and a quiet, dedicated workspace for remote work.

Round 1: Online assessment or screening questionnaire → Round 2: Functional interview (video auditing workflow, situational questions) → Round 3: HR interview (culture fit, availability, compensation discussion)

Amazon is a global e‑commerce and cloud‑computing giant that has redefined retail logistics through its massive fulfillment network. In India, Amazon operates dozens of fulfillment centers, leveraging cutting‑edge robotics, AI‑driven automation and a relentless focus on customer experience. The company’s culture of "customer obsession" and "invent and simplify" drives continuous innovation, making it one of the most sought‑after employers for fresh graduates. Amazon’s work environment encourages ownership, rapid learning, and the opportunity to impact millions of customers daily. The role of Associate, ML Data Operations – GO‑AI Operations is a contract position (6 months) that supports Amazon Robotics’ fulfillment centers by performing high‑volume video and image audits. Associates watch short stow‑action videos captured on the warehouse floor, use internal annotation tools to verify product placement, and flag any discrepancies. Their work directly feeds into Amazon’s machine‑learning models that automate stowing, thereby improving inventory accuracy and reducing operational defects. The position is primarily remote, with occasional on‑site days for training or team meetings, and requires a dedicated workspace with reliable internet connectivity. Key responsibilities: 1. Review 200‑300 short (15‑20 sec) stow videos per shift and accurately annotate product locations using Amazon’s proprietary tools. 2. Maintain a minimum accuracy threshold (typically >95%) while meeting productivity targets. 3. Identify and flag blurry or ambiguous footage, providing clear comments for further review. 4. Follow standardized SOPs for video auditing, ensuring consistency across the global operations team. 5. Log daily performance metrics and report any systematic issues to the team lead. 6. Adhere to rotational shift schedules, including night shifts, and take pre‑defined breaks to meet the 6.8‑7 hour productive window. 7. Keep the workstation secure; ensure that no unauthorized person accesses work‑related data. 8. Participate in virtual team meetings, keeping the laptop camera on when required. 9. Continuously improve speed and quality by incorporating feedback from coaching sessions. 10. Occasionally travel to a fulfillment center for on‑site training or audits as needed. Tech stack: The role does not require deep programming knowledge but familiarity with Windows OS, web‑based annotation platforms, basic spreadsheet tools, and reliable high‑speed internet is essential. Amazon’s internal video‑review tools are built on proprietary frameworks that integrate with AWS services. Growth path: High‑performing associates can transition to full‑time roles such as Data Analyst, Operations Analyst, or ML Data Engineer within Amazon’s fulfillment technology teams. The exposure to real‑world data labeling and robotics operations provides a solid foundation for careers in AI, supply‑chain analytics, or product management. Why join Amazon? You will be part of a world‑class organization that values data‑driven decision making and offers unparalleled learning opportunities. Even as a short‑term associate, you gain hands‑on experience with cutting‑edge automation technology, receive competitive compensation, and can build a network that opens doors to long‑term careers within Amazon’s vast ecosystem.