Associate ML Data Operations

Amazon is Hiring Associate ML Data Operations professionals to support its growing machine learning operations team. If you are looking for a non-technical role in data operations, this could be your best opportunity to join Amazon.

About Amazon

Amazon is a global technology company known for its e-commerce platform, cloud computing services (AWS), digital streaming, and artificial intelligence. Founded by Jeff Bezos in 1994, Amazon has become one of the world’s most valuable companies. It employs over 1.5 million people worldwide and continues to grow with its investments in logistics, AI, and retail.

Job Title: Associate ML Data Operations

Job Location: Work from Home (with occasional office visits)

Job Type: Contractual (6 months)

Department: Machine Learning Data Operations

Shifts: Rotational (including night shifts)

Work Schedule: 5 working days per week, with 2 consecutive days off (not necessarily on weekends)

Key Responsibilities of Associate ML Data Operations

H2: Associate ML Data Operations Responsibilities

• Watch hundreds of short videos during each shift.
• Provide accurate responses based on predefined quality standards.
• Maintain speed and productivity targets.
• Follow correct work practices and ensure proper workflow.
• Stick to scheduled breaks and spend 6.8 to 7 hours daily on video processing.
• Maintain data confidentiality and a distraction-free workspace.

H2: Eligibility Criteria

H3: Skills and Attributes

• Willingness to work in a non-technical role.
• Ability to audit image, video, and text-based jobs.
• Identify details even from blurry or low-resolution videos.
• High attention to detail and focus.
• Comfortable with shifting targets for quality and productivity.
• Fast-paced and consistent worker.
• Ability to work in remote teams.
• Ready to switch on the laptop camera during meetings.

H3: Work Environment

• Must have a dedicated table and chair setup.
• Adequate lighting and distraction-free environment required.
• No one else should access the workspace or data.
• Readiness to attend office occasionally as per business needs.

H2: A Day in the Life of an Associate ML Data Operations

• The associate works in a 24×7 rotational shift model.
• Each shift is 9 hours including pre-scheduled breaks.
• Shift schedules change every 3 to 4 months.
• Night shift allowance is provided as per Amazon policies.
• Associates get two consecutive weekly offs on a rotational basis.

H2: Why Join Amazon as Associate ML Data Operations?

• Get trained in Amazon’s machine learning ecosystem.
• Develop strong observational and data labelling skills.
• Work in a globally recognized organization.
• Exposure to a real-time ML data processing environment.
• Competitive pay and shift allowances.

H2: How to Apply for Amazon Associate ML Data Operations Role?

1. Visit the Amazon Jobs website.
2. Search for “Associate ML Data Operations.”
3. Click on the job posting.
4. Review all job details and requirements.
5. Click “Apply Now.”
6. Fill in the application form.
7. Upload resume and complete required assessments.

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H2: Top 10 Interview Questions for Associate ML Data Operations at Amazon

Q1: Why do you want to work at Amazon?

Answer: Amazon is a leading global company with a strong focus on innovation and technology. Working here provides a great learning environment and career growth.

Q2: What do you understand about the role of Associate ML Data Operations?

Answer: The role involves reviewing videos, identifying details, and tagging them correctly. It requires accuracy, consistency, and adherence to quality standards.

Q3: Are you comfortable working in rotational shifts, including night shifts?

Answer: Yes, I am fully comfortable with rotational shifts and can adapt to night shifts as per the requirement.

Q4: How do you maintain focus while reviewing multiple videos in a single shift?

Answer: I take short breaks during predefined slots and maintain a clean, quiet workspace. This helps in staying focused and maintaining accuracy.

Q5: Have you worked in a role requiring repetitive tasks? How did you manage it?

Answer: Yes, in my previous role, I handled repetitive data entry. I managed it through time management and periodic reviews to maintain productivity.

Q6: What would you do if you are unsure about a video’s content while tagging?

Answer: I would refer to the provided guidelines or ask a team lead or manager to ensure the correct response.

Q7: Can you work from home effectively and meet targets?

Answer: Yes, I have a dedicated workspace and high-speed internet. I am disciplined and ensure targets are met consistently.

Q8: What is your understanding of data privacy and confidentiality?

Answer: Data privacy means ensuring that work-related information is not accessed by unauthorized persons and is securely handled.

Q9: Are you willing to switch on your camera during virtual meetings?

Answer: Yes, I understand the need for face-to-face interactions and am comfortable turning on my camera during virtual calls.

Q10: Describe your experience with attention-to-detail tasks.

Answer: In my earlier roles, I’ve worked on reviewing forms and documents for accuracy, which helped me develop a strong attention-to-detail approach.

H2: Tips for Cracking Amazon Associate ML Data Operations Interview

• Understand the job responsibilities clearly.
• Be honest about your work-from-home setup.
• Practice staying focused on screen-intensive tasks.
• Review basic data labeling or tagging processes.
• Get familiar with confidentiality and data handling principles.

H2: Amazon Associate ML Data Operations – Summary

• Job Role: Non-technical
• Work Type: Remote with occasional office days
• Shift: Rotational, 24×7 support
• Duration: 6-month contract
• Skill Focus: Attention to detail, screen focus, accurate video tagging
• Work Culture: Fast-paced, target-driven, team-oriented

Final Words

Amazon is hiring Associate ML Data Operations professionals who can meet the company’s standards for quality, speed, and data handling. If you have the ability to stay focused and work accurately in a structured environment, this is your chance to become part of Amazon’s data operations team.

Apply Now