Associate, ML Data Operations, GO-AI Operations

AI in this role

Audits video and image data to support automation and inventory accuracy for Amazon Robotics fulfillment centers.

data-annotationvideo-auditingimage-annotationquality-assurance

This team enables automation at Amazon Robotics Fulfillment centers. This team serves Amazon Internal Fulfillment Technologies & Robotics teams by enabling automation, which includes real-time & offline (image/video) data auditing services. One of the key contributions of this team is supporting the fulfillment centers in maintaining inventory accuracy.

An Associate in this role is required to watch the video of the stowing action at a fulfillment center, understand it thoroughly and make best use of human judgement in combination with the tools and resources to indicate the activity captured in the video. They are expected to verify or mark the location of product through a tool while maintaining highest level of accuracy. This process helps in maintaining the fulfillment center's stow quality. This is an operational role. Under general supervision, the Associate performs precise and thorough video/image audits with high degree of accuracy and speed, thus aiding defect reduction.

Key job responsibilities
The Associate has to watch several hundred videos in a shift and provide responses by following goals on accuracy (quality), speed (productivity) and right / acceptable practices. Associates are required to take breaks at the pre-defined slots and ensure 6.8 to 7 hours’ time per day is spent to answer the videos. Associates who are hired to work from home should maintain (1) dedicated workspace i.e., table, chair & sufficient lighting (2) workspace / work related data shouldn’t be accessed by anyone other than employee

The candidate is expected to demonstrate:
• Willingness to work in Non-tech role for contract duration of 6 months
• Ability to audit image/video/text based Jobs
• Ability to identify details from blurry, less sharp videos and provide correct response. Requires high level of attention & focus on screen
• Willingness to work on incremental targets/goals on quality & productivity
• Fast Pace of implementation & consistent performance
• Ability to work in rotational shifts (including night shifts), remote teams and exceptionally good team player
• Readiness to come to office for few days (when required, applicable for associates working from home)
• Willing to switch ON laptop camera while on virtual meetings.

A day in the life
Associates work in 24x7 environment with rotational shifts. Associates would be working in a 9 hour shift, including pre-scheduled breaks. The shift timings would be subject to change every 3-4 months or as per business requirement. In case associate is working in night shift, night shift allowance will be provided as per applicable Amazon’s work policy.

Weekly Offs: Rotational two-consecutive day off (it is a 5-day working week with 2 consecutive days off, not necessarily Saturday and Sunday) or as per business discretion.

About the team
Data Auditing Operations team provides human support to Amazon Fulfillment facilities with goal of enabling hands-free active stowing through visual audits on videos/images. Videos with brief duration (typically between 15 and 20seconds) are sent to Operations Team for humans to audit them with information on products being stored at fulfilment centers. For business use, these videos must be thoroughly reviewed and audited using best human judgement. The effectiveness of automated process will be increased by using videos that Associates have audited. This process helps maintaining stow quality at fulfillment center and Associate will be further evaluated for performance improvements/coaching.

Basic qualifications

- Bachelor's degree

Preferred qualifications

- Work a flexible schedule/shift/work area, including weekends, nights, and/or holidays

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

How we rate this

Associate, ML Data Operations, GO-AI Operations at Amazon rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Key facts

Associate, ML Data Operations, GO-AI Operations is an open job at Amazon.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in IN, AP, Virtual and is marked remote.
The job was posted on October 5, 2026.
Seniority: junior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Data AnnotationVideo AuditingImage AnnotationQuality Assurance

Questions you could be asked

Tell me about a project where data annotation was part of your work. What did you do?
Tell me about a project where video auditing was part of your work. What did you do?
Tell me about a project where image annotation was part of your work. What did you do?
Tell me about a project where quality assurance was part of your work. What did you do?
Describe a typical day in a role like this one: which parts run through AI directly?

Adapt your resume

List these exact terms on your resume: Data Annotation, Video Auditing, Image Annotation, and Quality Assurance. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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