ML Data Associate I

Amazon’s interview process typically starts with an online assessment or screening questionnaire, followed by one or two technical/functional rounds that test domain knowledge, attention to detail, and communication skills. The final HR round evaluates cultural fit, motivation and availability. Candidates should be ready to discuss annotation examples, demonstrate clarity in following SOPs, and showcase Amazon’s leadership principles.

Amazon promotes a high‑performance culture where ownership and customer obsession are core values. Employees enjoy clear career ladders, frequent learning opportunities, and a collaborative environment that balances challenging projects with supportive leadership. While the pace is fast, the company emphasizes work‑life harmony through flexible shift options and robust employee benefits.

Bachelor's degree in any discipline; fluent in spoken, written and read English; proficient with Microsoft Office (Word, Excel, PowerPoint); no active backlogs; minimum 60% aggregate (preferred but not mandatory).

Round 1: Online assessment or screening questionnaire → Round 2: Functional interview focusing on annotation tasks, quality, and communication → Round 3: HR interview covering fit, availability and contract terms

Amazon, a global leader in e‑commerce and cloud computing, has built a reputation for relentless customer obsession and technological innovation. In India, Amazon operates massive fulfilment centres, a thriving retail ecosystem, and cutting‑edge research labs that power Alexa, computer‑vision services and smart‑device experiences. The company’s culture encourages ownership, bias for action, and a data‑driven mindset, making it an attractive destination for fresh talent eager to work on products that impact millions daily. The role of ML Data Associate I is a contract position (11 months) that sits at the heart of Amazon’s smart‑device and AI initiatives. As a data associate, you will be responsible for creating high‑quality ground‑truth data that trains and validates machine‑learning models used in devices such as Echo, Ring, and other IoT products. The work is hands‑on, repetitive yet intellectually stimulating, requiring strict adherence to guidelines, attention to detail, and strong command of English language conventions. Key responsibilities include: 1. Annotate audio, image, video and text files according to detailed SOPs, ensuring accurate labeling for model training. 2. Follow dynamic instructions and use internal annotation tools to capture data consistently. 3. Apply grammar, syntax and linguistic rules to maintain high‑quality textual outputs. 4. Comply with procedural, compliance and confidentiality requirements for each task. 5. Meet daily productivity and quality targets, reporting status through provided dashboards. 6. Conduct quality audits and verification to uphold internal standards. 7. Log and escalate any failures, doubts or queries via the portal within defined SLAs. 8. Participate in testing new SOPs and data‑collection tools, providing timely feedback. 9. Coordinate with internal and external stakeholders to resolve dependencies and ensure timely delivery. 10. Maintain zero‑risk handling of customer data and Amazon proprietary information. Tech stack: Amazon’s proprietary annotation platforms, basic scripting for data validation, Microsoft Office suite, and exposure to AI/ML pipelines such as SageMaker, computer‑vision libraries, and audio processing tools. Growth path: High performers can transition to roles like ML Data Engineer, Quality Analyst, or even Product Management within Amazon’s AI divisions, leveraging the experience gained in data labeling and quality assurance. Why join: Working at Amazon offers exposure to world‑class AI products, a fast‑paced learning environment, and the chance to contribute to technology that reaches millions. The contract also provides a stable income, access to Amazon’s learning resources, and the possibility of conversion to a permanent role based on performance.