Amazon is Hiring Associate, ML Data Operations (GO-AI) | Karnataka | Freshers (Contract)

Job Description

This Amazon listing deserves a clear heads-up before anything else: despite the 𝗠𝗟 𝗗𝗮𝘁𝗮 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀 title suggesting a machine learning role, this is explicitly stated in the posting itself as a 𝗡𝗼𝗻-𝘁𝗲𝗰𝗵 𝗿𝗼𝗹𝗲 — you would not be building or training ML models. Instead, you'd be manually watching hundreds of short warehouse videos per shift and labeling/verifying stow activity to generate training data that supports Amazon's robotics automation systems. This is 𝗵𝘂𝗺𝗮𝗻-𝗶𝗻-𝘁𝗵𝗲-𝗹𝗼𝗼𝗽 𝗱𝗮𝘁𝗮 𝗹𝗮𝗯𝗲𝗹𝗶𝗻𝗴 𝘄𝗼𝗿𝗸, a genuinely different job than the "ML" in the title implies, and worth understanding clearly before applying with technical AI/ML career expectations.

The role is also explicitly a 𝟲-𝗺𝗼𝗻𝘁𝗵 𝗰𝗼𝗻𝘁𝗿𝗮𝗰𝘁 𝗽𝗼𝘀𝗶𝘁𝗶𝗼𝗻, not a permanent hire — a detail stated directly in the requirements ("willingness to work in Non-tech role for contract duration of 6 months") that's easy to miss if you're skimming past the title toward the responsibilities. If you're evaluating this against permanent roles on other listings covered on this site, factor in that this is fixed-term work, not an ongoing position by default.

What the day-to-day actually looks like is repetitive, high-volume visual auditing: watching 15-20 second warehouse videos for hours at a stretch, marking product locations with high accuracy, under productivity and quality targets, in rotating 24x7 shifts (including nights). This is meaningfully different in nature from typical fresher "tech" roles — the core skill isn't technical knowledge but 𝘀𝘂𝘀𝘁𝗮𝗶𝗻𝗲𝗱 𝘃𝗶𝘀𝘂𝗮𝗹 𝗮𝘁𝘁𝗲𝗻𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗰𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝘁 𝗮𝗰𝗰𝘂𝗿𝗮𝗰𝘆 𝘂𝗻𝗱𝗲𝗿 𝘁𝗶𝗺𝗲 𝗽𝗿𝗲𝘀𝘀𝘂𝗿𝗲, closer to a specialized quality-control/BPO function than an engineering role.

𝗢𝘂𝗿 𝗧𝗮𝗸𝗲:

- 𝗚𝗼𝗼𝗱 𝗳𝗼𝗿: graduates (any degree, no technical background required) looking for a genuinely accessible entry point at Amazon, comfortable with repetitive, high-focus visual work and rotating shifts including nights

- 𝗡𝗼𝘁 𝗶𝗱𝗲𝗮𝗹 𝗳𝗼𝗿: those seeking ML/AI technical experience or career growth toward engineering roles — this role explicitly does not involve building or training models, and is a fixed 6-month contract rather than a growth-track position

- 𝗦𝗲𝗹𝗲𝗰𝘁𝗶𝗼𝗻 𝗱𝗶𝗳𝗳𝗶𝗰𝘂𝗹𝘁𝘆: likely lower relative to technical roles on this site — the qualification bar is simply a bachelor's degree, with the real screening happening around shift flexibility and sustained attention/accuracy under monitored performance metrics

- 𝗖𝗮𝗿𝗲𝗲𝗿 𝘁𝗿𝗮𝗷𝗲𝗰𝘁𝗼𝗿𝘆: this role is explicitly contract-based and non-technical, so it's best understood as a standalone opportunity rather than a stepping stone into Amazon's ML/engineering career tracks — worth being realistic about this before applying if long-term technical growth is your goal

𝗖𝗼𝗺𝗽𝗲𝗻𝘀𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝗻𝘁𝗲𝘅𝘁: Amazon hasn't disclosed pay for this role in the posting. Data annotation/operations associate contract roles at large tech companies in India typically range around ₹2–3.5 LPA equivalent (often structured as hourly or monthly contract pay) based on general market data for comparable data labeling/BPO-adjacent roles — this is an estimate only and should be confirmed directly during the application process.

𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆: Since the role doesn't require technical skills, your application and interview should focus on demonstrating reliability, sustained attention to detail, and comfort with structured, monitored work — mention any prior experience with detail-oriented, repetitive tasks under time pressure (quality control, proofreading, data entry) even outside a tech context, since that's a more relevant signal here than technical credentials.

Roles & Responsibilities

The role centers entirely on manual visual auditing at volume — watching, judging, and accurately labeling warehouse stow activity across hundreds of videos per shift, with strict adherence to accuracy and productivity targets.

- Watch stowing action videos at fulfillment centers and mark/verify product locations using an internal tool

- Maintain high accuracy while meeting speed and productivity goals across several hundred videos per shift

- Take pre-defined breaks and maintain 6.8–7 hours of active video-review time per day

- Work rotational shifts, including nights, in a 24x7 environment with rotating weekly offs

- Maintain a dedicated, private workspace if working from home and keep the camera on during virtual meetings

Qualifications & Eligibility

Minimal formal requirements — this role is accessible to any graduate regardless of technical background, with the real qualifying factors being behavioral and logistical rather than academic.

- Bachelor's degree (any discipline)

- Willingness to work a 6-month contract in a non-technical role

- Ability to work flexible schedules, including nights, weekends, and holidays

Skills Required

No technical skills are required — the core competencies are attentional and behavioral rather than knowledge-based.

- Ability to accurately audit image/video/text-based content, including identifying details in blurry or unclear footage

- Sustained attention and focus for extended screen-based work

- Comfort with incremental performance targets on quality and productivity

- Strong teamwork ability within remote, rotational-shift teams