| Job Type | Full-time, Associate level |
|---|---|
| Work Mode | On-site, rotational schedule (including weekends and/or holidays) |
| Expected Salary | ₹4 – ₹8 LPA |
| Basic Qualification | Bachelor’s degree, MS Office familiarity, English at CEFR B2 (Intermediate) or C1 (Advanced) |
| Preferred | Master’s in Computational Linguistics; 1+ years ML Data Operations experience |
Amazon has opened an ML Data Associate position within its Devices team — the group behind smart home products that use AI, computer vision, sensor technology, and edge computing for security, monitoring, and staying connected with family. This role sits behind the scenes of those products: you’d be doing the annotation work that trains and validates the AI models powering them, not building the devices or writing the AI algorithms yourself.
What “annotation-related tasks” actually means day to day
Strip away the job-title language, and the core work is labeling and reviewing data — audio, image, video, and text files — so Amazon’s machine learning models can learn from accurate, human-verified examples. This is detail-oriented, instruction-driven work: you’d follow defined guidelines precisely, apply genuine linguistic and grammar awareness when the task involves text, and maintain consistent quality across repetitive tasks — closer to meticulous, structured data work than a creative or open-ended role.
The full scope of responsibilities
- Performing annotation tasks across audio, image, video, and text files, following defined instructions to collect accurate ground truth data
- Executing structured, detail-oriented exercises based on evolving instructions using internal software tools and data capture systems
- Applying language skills, grammar knowledge, and linguistic awareness to ensure generated text follows proper syntax and usage
- Understanding and following procedures, guidelines, and compliance requirements for new tasks and releases
- Meeting daily productivity and quality targets, tracking status using recommended tools and reporting individually
- Performing quality audits and verification activities to maintain high internal process standards
- Capturing and reporting results accurately, escalating concerns promptly through established channels
- Raising questions or issues through the designated portal, resolving them per defined SLAs
- Taking ownership of daily targets and managing both internal and external dependencies for timely completion
- Adhering strictly to confidentiality and compliance requirements given the customer data involved
- Helping test new SOPs and ML data tools, providing specific, timely feedback to improve processes
A genuinely important practical requirement
This role explicitly requires flexibility for a rotational schedule, including weekends and/or holidays — not a standard fixed Monday-to-Friday role. Familiarity with US culture is also listed as an added advantage, which makes sense given this work likely supports Amazon’s US-market smart device products and their English-speaking customer base specifically.
Qualifications, clearly separated
Basic (required): A Bachelor’s degree, working knowledge of Microsoft Office products, and advanced English language skills at CEFR level B2 (Intermediate) or C1 (Advanced) — genuinely strong English proficiency, not basic conversational ability.
Preferred (advantageous, not mandatory): A Master’s degree or above in Computational Linguistics, and a minimum of 1+ years of experience in ML Data Operations specifically.
FAQs
1. Is this a coding or software engineering role?
No — this is a data annotation and quality-review role. You’d be labeling and verifying audio, image, video, and text data that trains Amazon’s AI models, not writing the underlying machine learning code.
2. Is a Master’s degree required to apply?
No — a Bachelor’s degree is the basic qualification. A Master’s in Computational Linguistics is listed under Preferred Qualifications, meaning it strengthens an application but isn’t mandatory.
3. Does this role have fixed weekday working hours?
No — the listing explicitly requires flexibility for a rotational schedule, including weekends and/or holidays, so candidates should not expect a standard Monday-to-Friday routine.
4. Is the salary for this role officially confirmed by Amazon?
No — Amazon’s listing doesn’t publish a figure. The ₹4–8 LPA range is consistently reported across Glassdoor, AmbitionBox, and independent job platforms specifically for this role, making it a reasonably reliable estimate.
About Amazon
amazAmazon is one of the world’s leading technology and e-commerce companies, known for online shopping, cloud computing, artificial intelligence, and digital streaming services. The company operates globally and provides innovative solutions through platforms like Amazon Web Services (AWS). Amazon offers a fast-paced, customer-focused work environment where employees work on advanced technologies, business operations, and innovative projects while gaining valuable learning...
View Company Profile →Top Interview Questions
Prepare with commonly asked questions for this role
I'd apply the closest applicable guideline as a baseline, document the ambiguity clearly, and flag it through the designated portal rather than guessing silently — consistency and traceability matter more than moving fast on an unclear case.
Be honest and specific — reference any relevant coursework, certifications, or practical experience using advanced English professionally, since this is an explicit, tested requirement rather than a soft preference.
Reference genuine habits — regular short breaks to reset focus, periodic self-checks against guidelines, and tracking your own error patterns — since sustained accuracy on repetitive work is a core, explicitly tested trait for this role, not incidental.
Answer honestly based on your actual circumstances — Amazon states this requirement explicitly upfront, so a genuine, considered response matters more than agreeing without thinking through the real, ongoing impact on your schedule.
This data often comes from real customers' smart home devices — audio, video, images from their actual homes — so mishandling it isn't a minor slip, it's a genuine privacy and trust issue. Emphasize concrete habits: following data-handling protocols precisely and never discussing specifics outside authorized channels.