Amazon hiring for Associate, ML Data Operations, GO-AI Operations, Job ID 3134253. Check degree eligibility, video auditing duties, shifts, work-from-home conditions and application details. Are you looking for an opportunity to work with Amazon in a non-technical operations role involving artificial intelligence, image and video auditing, and data quality? Amazon has listed an Associate, ML Data Operations – GO-AI Operations position under Job ID 3134253. The role supports Amazon Robotics and fulfilment centre automation by helping teams review visual data and maintain inventory and stowing accuracy.
This position combines human judgement with specialised tools to review short videos, identify product-stowing activities, and mark or verify product locations. Associates are expected to maintain high accuracy, meet productivity targets, follow established procedures, and work effectively in a fast-paced operational environment.
The supplied job description specifies a six-month contract duration for the non-technical role. It also describes rotational shifts, including night shifts, a nine-hour shift including scheduled breaks, and the possibility of working from home depending on the assigned arrangement. Candidates working remotely must maintain a dedicated workspace and protect work-related information.
The basic educational requirement is a bachelor’s degree. Candidates should also be comfortable with repetitive visual-auditing tasks, extended screen focus, performance targets, and schedule flexibility.
Amazon Associate, ML Data Operations – Job Overview
| Job Detail | Information |
|---|---|
| Company | Amazon |
| Job Title | Associate, ML Data Operations |
| Team | GO-AI Operations |
| Job ID | 3134253 |
| Business Entity | ADCI – Karnataka – A66 |
| Department/Function | Data Auditing Operations |
| Job Category | Applied Science, as displayed on the job page |
| Role Type | Non-technical operational role |
| Basic Qualification | Bachelor’s degree |
| Contract Duration | Six months, as stated in the supplied description |
| Primary Work | Image and video auditing, visual data verification and product-location marking |
| Work Arrangement | Virtual options are listed; Bengaluru is also listed as a location |
| Shift | Rotational shifts, including night shifts |
| Shift Duration | Nine hours including scheduled breaks |
| Video-Auditing Time | Approximately 6.8–7 hours per day, as specified in the description |
| Weekly Offs | Two consecutive rotational days off, subject to business requirements |
| Salary | Not specified in the supplied description |
| Night-Shift Allowance | Provided according to applicable Amazon policy when assigned to night shifts |
| Application Mode | Online |
| Official Application |
The official listing identifies Bengaluru, Hyderabad – Virtual, Bangalore – Virtual, Chennai – Virtual, and Andhra Pradesh – Virtual among its listed location options. Applicants should confirm the available location and work arrangement applicable to their application. <Cite refs={[“turn498176view0”]}/>
Note: The job page does not specify a salary amount or application deadline in the supplied information. Check the official portal for the current vacancy status and any additional conditions.
About Amazon
Amazon hiring for Associate, ML Data Operations, GO-AI Operations, Job ID 3134253. Check degree eligibility, video auditing duties, shifts, work-from-home conditions and application details. is a global technology and commerce company with operations spanning online retail, logistics, cloud computing, fulfilment networks, and automation technologies.
Its fulfilment centres handle large volumes of products and rely on accurate inventory records, efficient storage processes, and reliable operational systems. Robotics and automation help support these activities, but automated systems also depend on good-quality data.
Visual data can help teams understand what happens during a physical process. When a product is placed in a storage location, for example, a video may show the product, the movement involved, and the location where the item was stored.
The Associate, ML Data Operations role supports this process by reviewing image and video data and recording accurate information through designated tools.
This human review helps Amazon’s internal Fulfilment Technologies and Robotics teams improve automated processes and maintain fulfilment centre quality.
What Is the GO-AI Operations Team?
GO-AI Operations supports Amazon’s efforts to expand automation through human-in-the-loop data operations.
Human-in-the-loop means that people participate in a process that also uses automated systems or machine learning technologies. Human judgement helps review information, label examples, validate outputs, and identify errors that may require correction.
In this role, associates examine short videos showing stowing activities at fulfilment centres. They review what is happening, interpret the visual information, and use a specialised tool to identify or mark product locations.
The reviewed information can support improvements in automated stowing and inventory accuracy.
The role is operational rather than a conventional software development position. Candidates do not need to assume that they will be building AI models or writing machine learning code simply because the job title includes “ML Data Operations.”
Instead, the key responsibility is to provide reliable human-reviewed data that supports automation and quality improvement.
Job Description: Associate, ML Data Operations
The Associate, ML Data Operations position involves carefully reviewing visual information and recording accurate responses according to established guidelines.
Associates watch videos of product-stowing activities and determine what the footage shows. They use available tools and resources to verify or mark product locations and submit responses.
The role requires a combination of attention to detail, visual observation, consistency, judgement, and productivity.
A typical task may involve watching a short video, understanding the movement or storage activity, identifying the relevant product location, and recording the answer in the assigned system.
Because the work supports inventory accuracy and automated processes, errors can affect data quality. Associates must therefore balance speed with accuracy rather than simply completing as many videos as possible.
The role also includes performance monitoring and coaching. Associates may receive feedback about accuracy, productivity, and adherence to required procedures.
Roles and Responsibilities
1. Review image and video data
One of the main responsibilities is reviewing images and videos captured during fulfilment centre operations.
The supplied description says videos are typically around 15–20 seconds long. Associates must observe each clip carefully and understand the activity shown.
They need to identify relevant visual details before entering a response. This requires concentration and the ability to follow the assigned workflow consistently.
2. Identify product-stowing activities
Stowing refers to placing products into designated storage locations within a fulfilment centre.
Associates watch the footage to understand the stowing action and determine what the video indicates about the activity.
They must interpret the visual information according to the guidelines provided by Amazon. When a video is unclear, they should use the available tools and instructions rather than guess.
3. Mark or verify product locations
Associates use a specialised tool to indicate or verify where a product is located.
Accurate location marking helps maintain reliable records of product-stowing activity. It also contributes to the quality of the data used by automation systems.
The exact software interface and annotation tools are not named in the supplied job description.
4. Maintain high accuracy
Accuracy is a major performance expectation.
An incorrect answer may introduce an error into the audited data. Associates should therefore observe the relevant details, follow the instructions, and verify their response before submitting it.
Maintaining accuracy requires consistency even when the work involves hundreds of videos during a shift.
5. Meet productivity targets
The job description states that associates must review several hundred videos in a shift and meet productivity goals.
Productivity expectations mean completing assigned work at the required pace while maintaining quality.
Candidates should understand that the role may involve repetitive tasks and structured performance monitoring. The precise number of videos expected may depend on the applicable workflow and targets.
6. Identify details in blurry videos
Some videos may be blurry, less sharp, or difficult to interpret.
Associates must use careful observation and human judgement to identify the relevant information as accurately as possible.
This requires patience, visual attention, and the ability to concentrate on small details. It is important not to invent an answer when the footage does not clearly support it; associates should follow the prescribed procedure for ambiguous cases.
7. Follow standard operating procedures
The role requires following established rules and acceptable work practices.
Standard operating procedures help ensure that different associates evaluate similar situations consistently.
Candidates should be prepared to learn detailed instructions, follow them accurately, and adapt when approved guidelines or tools change.
8. Support defect reduction
Visual audits help identify errors and improve the quality of information used by automated processes.
Accurate human-reviewed data can help teams understand whether automated processes are operating as expected and where improvements may be needed.
The associate contributes by performing reliable audits, recording accurate responses, and following quality standards.
9. Maintain focus throughout the shift
The job requires a high level of attention and screen focus.
Associates may review many short clips in succession. They must remain attentive even when the videos show similar activities or contain limited visual information.
Following scheduled breaks and maintaining a consistent work routine can help support accuracy and productivity.
10. Adapt to changing targets and workflows
The description highlights incremental targets and changing quality and productivity goals.
Associates should be ready to learn updated instructions, use revised tools, and adapt to operational requirements.
The ability to accept coaching and improve performance is important in this environment.
11. Work with remote teams
The role requires the ability to collaborate with remote teams and contribute effectively to a team environment.
Associates should communicate clearly during virtual meetings, follow instructions, share relevant information, and respond appropriately to feedback.
Remote work still requires professionalism, accountability, and adherence to work schedules.
12. Protect work-related information
Associates hired to work from home must maintain a dedicated workspace. The description specifically mentions a table, chair, and sufficient lighting.
It also states that the workspace and work-related data must not be accessible to anyone other than the employee.
This means candidates should be prepared to work in a private, controlled environment and follow Amazon’s information-security requirements.
13. Attend office when required
Even associates working from home may be asked to visit an office for a few days when required.
Candidates should consider this condition before applying and confirm any location-specific expectations during recruitment.
14. Participate in virtual meetings
The supplied job description states that associates must be willing to switch on their laptop camera during virtual meetings.
Candidates should be comfortable participating in virtual meetings and following the communication and security requirements established by the team.
15. Participate in coaching and performance improvement
The description says associates may be evaluated for performance improvement and coaching.
This means performance feedback can be part of the role. Associates should use feedback to understand mistakes, improve consistency, and meet the required standards.
Eligibility Criteria
Educational qualification
The basic qualification is a bachelor’s degree.
Candidates should verify that their degree meets Amazon’s requirements and ensure that their education details are accurate in the application.
The supplied description does not specify a mandatory degree specialisation or graduation year.
Willingness to work in a non-technical role
The job description explicitly asks candidates to be willing to work in a non-technical role for the stated six-month contract duration.
Although the work supports machine learning and automation, the day-to-day activities focus on auditing visual data rather than developing software or training models directly.
Candidates should apply with a clear understanding of the actual work.
Attention to detail
Attention to detail is essential when reviewing videos and marking product locations.
Applicants should be comfortable observing visual information carefully, identifying differences, and following detailed instructions.
Ability to maintain accuracy
The role has quality targets. Candidates need to prioritise correctness while working at the expected pace.
The ability to remain consistent across repetitive tasks is particularly relevant.
Comfort with extended screen work
The job requires several hours of daily video auditing. Candidates should understand the screen-focused nature of the work and the prescribed break schedule.
Shift flexibility
The position operates in a 24-hour, seven-day environment. Associates may be assigned rotational shifts, including night shifts, weekends, or holidays.
Applicants should be prepared for schedule changes according to business requirements.
Teamwork
Candidates must work effectively with colleagues and remote teams. Communication, cooperation, and willingness to follow shared procedures are important.
Work-from-home readiness
For a remote assignment, candidates must maintain an appropriate workspace and protect work-related data.
They should also be prepared to attend the office when required and participate in virtual meetings according to team expectations.
Is This a Technical or Non-Technical Job?
This is a non-technical operational role according to the supplied description.
The role supports machine learning and robotics initiatives, but its main tasks are reviewing videos, auditing data, identifying activities, marking product locations, and maintaining quality.
It is different from roles such as machine learning engineer, data scientist, software developer, or robotics engineer.
| Area | This Role |
|---|---|
| Primary work | Visual data auditing |
| Coding | Not specified as a requirement |
| Machine learning model development | Not described as a responsibility |
| Image/video review | Core responsibility |
| Data annotation or marking | Part of the workflow |
| Accuracy targets | Required |
| Productivity targets | Required |
| Technical tools | Specialised auditing tools; exact names not specified |
| Work type | Operational |
| Contract | Six months, as stated in the supplied description |
Candidates interested in gaining exposure to AI-related operations may consider the position. However, anyone seeking a coding-focused job should carefully compare the responsibilities with their long-term career goals.
What Is Human-in-the-Loop Data Auditing?
Human-in-the-loop data auditing combines automated technology with human review.
An automated system may process visual data, but human judgement can help validate the information, identify mistakes, and provide reliable examples for improving future performance.
In the context of this role, associates review videos of stowing actions and mark the relevant product location or activity.
The audited data helps support quality assurance and automation efforts. If the human review is accurate and consistent, it can provide useful information for evaluating and improving automated workflows.
The role demonstrates how operational teams can support AI-related systems without necessarily writing code or developing models.
Understanding the Work Schedule
The supplied job description provides several important schedule details.
Nine-hour shift
Associates work a nine-hour shift that includes pre-scheduled breaks.
The actual schedule depends on the assigned shift and business requirements.
Video-auditing time
The description says associates should spend approximately 6.8–7 hours per day answering videos, with breaks taken at predefined times.
Rotational shifts
The operation runs 24 hours a day, seven days a week. Shifts may include night work.
The description says shift timings may change every three to four months or according to business requirements.
Weekly offs
The listing describes a five-day working week with two consecutive rotational days off, subject to business discretion. These days are not necessarily Saturday and Sunday.
Night-shift allowance
The description states that a night-shift allowance is provided when applicable under Amazon’s work policy.
The amount and eligibility conditions are not disclosed in the supplied information.
Candidates should confirm the actual shift, weekly-off pattern, break timings, and applicable allowance during recruitment.
Work From Home: Important Conditions
The job listing includes virtual location options, but candidates should confirm the exact arrangement offered for their application.
If assigned to work from home, the supplied description requires the following:
- A dedicated workspace with a table, chair, and sufficient lighting.
- Work-related data and the workspace must not be accessible to other people.
- Willingness to attend the office for a few days when required.
- Willingness to turn on the laptop camera during virtual meetings.
- Ability to work with remote teams and follow assigned shifts.
Before applying, consider whether your home environment can meet these conditions consistently.
Do not assume that every applicant will automatically receive a permanent work-from-home arrangement simply because virtual locations are displayed.
Salary and Benefits
The supplied job description does not state an exact salary or monthly compensation amount.
It does mention that a night-shift allowance will be provided according to the applicable Amazon policy when an associate works a night shift.
Candidates should not rely on salary figures from unrelated job listings or unofficial sources as confirmation of compensation for this requisition.
Before accepting an offer, confirm:
- Monthly gross salary.
- Estimated monthly take-home pay.
- Applicable night-shift allowance.
- Contract duration and employment terms.
- Leave and weekly-off policy.
- Any applicable benefits.
- Equipment and connectivity requirements.
- Work location and remote-work conditions.
The recruitment team should confirm the exact compensation package and terms for Job ID 3134253.
Skills to Highlight in Your Resume
A resume for this position should emphasise skills that match the actual operational responsibilities.
Attention to detail
Include genuine examples where you checked information carefully, identified errors, or completed a task requiring accuracy.
Visual observation
If you have experience with image review, video review, quality checks, or visual inspection, describe it accurately.
Do not claim professional annotation experience unless you have actually performed it.
Concentration and consistency
Explain how you manage repetitive work while maintaining quality, if you have relevant examples from academic, professional, or other activities.
Following instructions
Demonstrate your ability to learn procedures and follow detailed guidelines.
Time management
Mention genuine examples of completing work within deadlines while maintaining quality.
Teamwork and communication
Include examples of collaborating on assignments, communicating progress, or responding constructively to feedback.
Adaptability
Describe situations where you learned a new process or adjusted to changing requirements.
Keep your resume concise and truthful. Do not add technical skills merely because the role includes “ML” in its title.
Interview Preparation
The supplied job description does not provide an official interview question list or confirm a specific selection process. The following are practice questions based on the responsibilities of the role.
1. What do you understand about this position?
Explain that the role involves auditing images and videos of fulfilment centre activities, identifying product-stowing information, marking or verifying product locations, and maintaining quality and productivity targets.
2. Why are you interested in this role?
Discuss your interest in operational work, attention to detail, learning new tools, and contributing to AI-supported automation processes.
Be honest about your understanding of the non-technical nature of the job.
3. How would you handle a blurry video?
Explain that you would review the clip carefully, use the approved tools and instructions, and follow the defined procedure if the information remains unclear rather than guessing.
4. How would you balance speed and accuracy?
Explain that you would learn the workflow, follow a consistent review method, use the available guidance, and monitor both accuracy and productivity.
5. Are you comfortable with repetitive work?
If true, explain how you maintain concentration during repeated tasks and use the prescribed breaks to manage your work routine.
6. Are you willing to work rotational night shifts?
Answer honestly based on your availability and personal circumstances. The listing specifically states that rotational shifts may include nights.
7. Can you work from home under security requirements?
Explain whether you can maintain a dedicated workspace and prevent other people from accessing work-related data.
8. How do you respond to feedback?
Give a genuine example of receiving feedback, correcting an issue, and improving your work.
9. What would you do if you were unsure about a product location?
Explain that you would review the video and instructions, use approved tools, and follow the escalation or uncertainty procedure established by the team.
10. How do you work with a remote team?
Discuss clear communication, following instructions, attending meetings, sharing progress, and completing assigned tasks reliably.
How to Apply for Amazon Associate, ML Data Operations
Follow these steps to apply through the official Amazon Jobs portal.
Step 1: Open the official job listing
Visit:
Step 2: Verify the requisition
Confirm the job title and Job ID 3134253.
Step 3: Check the qualification
Ensure that you meet the bachelor’s degree requirement.
Step 4: Review the work conditions
Read the details about the six-month contract, rotational shifts, video-auditing workload, remote-work conditions, and possible office visits.
Step 5: Prepare your resume
Highlight relevant accuracy-focused work, attention to detail, communication, teamwork, and ability to follow procedures.
Step 6: Submit your application
Use the official application process and provide accurate education and personal details.
Step 7: Monitor your application
Check your registered email and phone for recruitment communications and follow any instructions provided by Amazon.
Step 8: Confirm the offer terms
Before accepting, verify the salary, contract duration, shift assignment, work location, remote-work conditions, and applicable benefits.
Frequently Asked Questions (FAQs)
1. What is the job title?
Associate, ML Data Operations – GO-AI Operations.
2. What is the job ID?
The job ID is 3134253.
3. What is the qualification required?
A bachelor’s degree is the basic qualification listed in the supplied job description.
4. Is this a technical job?
No. The supplied description explicitly identifies it as a non-technical operational role.
5. What is the contract duration?
The description states a six-month contract duration for this role.
6. Is work from home available?
Virtual location options are listed. The exact work arrangement depends on the applicable vacancy and assignment. Remote associates must maintain a dedicated workspace and protect work-related data.
7. What are the main responsibilities?
The main tasks include watching videos, auditing visual data, identifying stowing activities, marking product locations, and maintaining accuracy and productivity targets.
8. Are coding skills required?
The supplied description does not list programming or coding as a mandatory requirement.
9. Are night shifts compulsory?
The role operates in a 24/7 environment with rotational shifts, including night shifts. Candidates should be prepared for schedule flexibility and confirm their assignment with the recruiter.
10. What are the working hours?
The description specifies a nine-hour shift including scheduled breaks, with approximately 6.8–7 hours per day spent answering videos.
11. Are Saturday and Sunday always off?
No. The description specifies two consecutive rotational days off, not necessarily Saturday and Sunday.
12. Is a night-shift allowance available?
The supplied description says an allowance will be provided according to applicable Amazon policy when an associate works a night shift.
13. What is the salary?
The supplied description does not disclose an exact salary. Confirm the compensation with Amazon.
14. Does the role involve AI?
Yes, it supports Amazon Robotics and automation initiatives by providing human-reviewed visual data. However, the role itself is operational and does not describe machine learning model development as a responsibility.
15. Where can I apply?
Apply through the official Amazon Jobs page: Click here
Final Words
The Amazon Associate, ML Data Operations – GO-AI Operations opportunity is intended for candidates with a bachelor’s degree who are comfortable with a non-technical, accuracy-focused operational role.
The work supports Amazon Robotics and fulfilment centre automation through image and video auditing, product-location verification, and quality control. Candidates should be prepared for repetitive screen-based tasks, productivity targets, rotational shifts, and the stated six-month contract duration.
Before applying, review the official listing carefully and confirm the current vacancy status, work arrangement, compensation, and contract conditions.
