Amazon is hiring For ML Data Associate Role | Amazon Recruitment 2025 – Apply Now

Amazon is hiring for ML Data Associate Role 

About Company :

Amazon, a global technology giant, is hiring for ML Data Associate roles. The company is driven by four principles: customer obsession, passion for invention, commitment to operational excellence, and long-term thinking. Amazon strives to be Earth’s most customer-centric company, innovating across e-commerce, cloud computing (AWS), digital streaming, and AI. ML Data Associates contribute directly to improving Amazon’s AI/ML models, such as those powering Alexa or search services, by providing crucial data annotation and analysis. This role is fundamental to enhancing customer experience and advancing AI technologies within the company

Official Company Website : www.amazon.in

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Amazon is hiring for ML Data Associate Role  Position:

Job Description :

Amazon’s ML Data Associate role involves analyzing and annotating various data types (text, speech, images) to train and improve Machine Learning models, such as those for Alexa. You’ll execute test case instructions, identify data patterns/discrepancies, and ensure high-quality data labeling according to guidelines. Responsibilities include using in-house software, reporting tool issues, contributing to process improvements, and maintaining strict confidentiality. This role requires strong attention to detail, adherence to daily deadlines, and a proactive approach to delivering accurate data that enhances Amazon’s AI capabilities.

Minimum Qualifications:

• Bachelor’s degree in any discipline, 0-2 years of work experience with strong task execution abilities, excellent computer skills, a high typing speed, strong research capabilities, and proficiency in English (minimum B2 level in the CEFR framework). 

Job function: ML Data Associate I

Skills/experience:

• High Attention to Detail: Critical for accurate data annotation and identifying subtle patterns or discrepancies.
• Strong Analytical and Problem-Solving Skills: Ability to analyze data, evaluate information, and make sound judgments, even with ambiguous input.
• Excellent Computer Proficiency: Familiarity with Windows desktop environment, and strong working knowledge of Microsoft Office Suite (Word, Excel) and web browsers.
• High Typing Speed and Accuracy: Essential for efficient data entry and processing.
• Strong English Language Skills: Proficiency in both written and verbal English (minimum B2 level CEFR) for understanding guidelines and internal communication.
• Research Capabilities: Proven ability to conduct comprehensive research and evaluate diverse subject matters when required.
• Adaptability and Flexibility: Comfort working in a fast-paced, dynamic, and ever-changing environment with shifting priorities.
• Confidentiality Adherence: Strict commitment to maintaining confidentiality and following all data security protocols.
• Ability to Follow Guidelines: Meticulous adherence to established guidelines and standard operating procedures for data labeling and quality.

Responsibilities:

• Data Annotation and Labeling: Accurately analyze and annotate large volumes of diverse data (e.g., text, speech, images, video) according to specific guidelines.
• Test Case Execution: Execute detailed test case instructions for evaluating data quality and model performance.
• Pattern Identification & Discrepancy Reporting: Proactively identify linguistic patterns, edge cases, and data discrepancies, and report them to the relevant teams.
• Tool Usage & Feedback: Efficiently utilize in-house annotation and data analysis tools, and provide constructive feedback on tool usability and functionality.
• Process Improvement Contribution: Actively participate in improving existing data annotation processes and contributing to the development of new guidelines.
• Quality Assurance: Ensure the highest quality and accuracy of annotated data, rigorously adhering to established standards and deadlines.
• Guideline Adherence: Strictly follow complex and evolving guidelines for data labeling, ensuring consistency and precision.
• Confidentiality Maintenance: Uphold strict confidentiality regarding all project data and proprietary information.
• Issue Reporting: Clearly document and report any issues, ambiguities, or technical problems encountered during data processing.

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Education requirements:

• Bachelor’s Degree: A Bachelor’s degree in any discipline is generally the fundamental requirement.
• No Specific Field: The degree can be from any field of study; it doesn’t necessarily need to be technical or computer science-related.
• Fresh Graduates Welcome: This role often targets fresh graduates or individuals with minimal prior work experience (e.g., 0-2 years).
• Strong Academic Background: While not always explicitly stated with a GPA, a decent academic record is generally preferred.
• English Proficiency: Demonstrated strong proficiency in English, often specified as B2 level or higher in the CEFR framework.
• Computer Literacy Courses/Experience: While not a formal degree, any coursework or strong practical experience demonstrating computer literacy is highly beneficial.
• Analytical Training: Exposure to subjects or projects requiring analytical thinking and data interpretation, even if not a formal data science degree.
• Communication Skills Focus: Education or experience that has honed strong written and verbal communication skills.
• Interest in AI/ML: Though not a formal education requirement, a keen interest in Machine Learning, AI, and data annotation is often an unstated preference.