Associate, ML Data Operations, GO-AI Operations

Candidates typically face an online assessment that tests logical reasoning and basic data interpretation, followed by a role‑specific interview focusing on video‑audit scenarios, attention to detail, and situational judgment. The final HR round evaluates cultural fit, shift flexibility, and communication skills. Preparation should include practicing visual‑analysis tasks and reviewing Amazon's leadership principles.

Amazon Dev Center India fosters a culture of innovation, ownership, and relentless customer focus. Employees benefit from clear career ladders, frequent learning opportunities, and a supportive environment that values diverse perspectives. While the pace is fast, the company emphasizes work‑life balance through flexible shift patterns and comprehensive employee benefits.

Bachelor's degree in any discipline; no minimum CGPA specified; no active backlogs; eligibility for fresh graduates of 2024‑2026 batches.

Round 1: Online assessment → Round 2: Technical/role‑specific interview → Round 3: HR interview

Amazon Dev Center India is a key technology hub for one of the world’s most customer‑obsessed companies. The centre drives innovation across e‑commerce, cloud services, and artificial intelligence, delivering solutions that power millions of daily transactions. With a strong focus on diversity, inclusion, and continuous learning, Amazon provides a vibrant environment where fresh talent can grow alongside seasoned engineers and data scientists. The company’s culture emphasizes ownership, bias for action, and a relentless pursuit of operational excellence, making it an attractive destination for ambitious graduates. The role of Associate, ML Data Operations, GO‑AI Operations is an operational yet highly impactful position. Associates are tasked with reviewing short video clips (typically 15‑20 seconds) captured from Amazon Robotics fulfillment centers. Each video shows a stowing action, and the associate must accurately identify product placement, verify location tags, and flag any anomalies. This human‑in‑the‑loop auditing feeds directly into Amazon’s machine‑learning pipelines, helping improve the accuracy of automated stow quality checks. The work demands sharp visual attention, quick decision‑making, and consistent adherence to quality and productivity targets. Key responsibilities include: 1. Watch and audit several hundred short videos per shift, ensuring high accuracy and speed. 2. Use proprietary tools to mark product locations and record observations. 3. Maintain a minimum of 6.8‑7 hours of active video‑review time per day, adhering to pre‑defined break schedules. 4. Identify details in low‑resolution or blurry footage and provide correct judgments. 5. Meet incremental quality and productivity targets set by the operations lead. 6. Work rotational shifts, including night shifts, with appropriate night‑shift allowances. 7. Collaborate with remote teammates, sharing best practices and feedback. 8. Occasionally attend on‑site days for training or process alignment. 9. Keep the laptop camera on during virtual meetings for compliance. 10. Follow data‑security protocols, ensuring workspace privacy and confidentiality. The tech stack is lightweight for this role, primarily involving a web‑based annotation platform, basic data‑visualisation dashboards, and secure VPN access. While no deep programming is required, familiarity with spreadsheet tools and a comfort level with digital interfaces is beneficial. Growth paths can lead to senior data‑auditor positions, quality‑engineer roles, or transition into more technical ML‑data‑pipeline positions after gaining domain expertise. Joining Amazon offers exposure to cutting‑edge logistics automation, a clear career ladder, and the chance to contribute directly to the efficiency of one of the world’s largest fulfillment networks. The role is ideal for recent graduates who thrive in fast‑paced, detail‑oriented environments and are eager to see their work influence large‑scale operational outcomes.