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Data Annotation Services Jobs (NOW HIRING)

JPMorganChase

Data Domain Architect Lead

Wilmington, DE · On-site

JPMorganChase is a leading financial services firm, helping nearly half of America's households and ... annotation, curation, and validation while collaborating with other teams to optimize training data ...

BC Forward

AI Data Annotation Specialist

Charlotte, NC · On-site

$65.05/hr

Founded in 1998, BCforward has grown with our customers needs into a full-service business ... Collaborate with data science and platform teams to deploy scalable AI solutions. Annotate and ...

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Data Annotation Services information

How hard is it to get hired by data annotation?

Getting hired for data annotation services typically requires basic computer skills, attention to detail, and the ability to follow instructions. Many positions are entry-level and may not require prior experience, but familiarity with annotation tools and good accuracy can improve chances of employment.

What are the key skills and qualifications needed to thrive in Data Annotation Services, and why are they important?

To excel in Data Annotation Services, strong attention to detail, data literacy, and a foundational understanding of data labeling processes are essential, often requiring a high school diploma or equivalent. Familiarity with annotation platforms, labeling tools, and sometimes basic knowledge of scripting or data management systems is typically expected. Strong work ethic, consistency, and effective communication skills help individuals stand out in collaborative, deadline-driven environments. These capabilities ensure high-quality, accurate labeled data, which is critical for training reliable machine learning models.

Does data annotation actually pay you?

Data annotation services typically pay workers for labeling data used in machine learning models. Payment rates vary depending on the platform, task complexity, and experience, with many jobs offering hourly or per-task compensation. Reliable platforms often require basic skills in data handling and attention to detail.

Is data annotation real or fake?

Data annotation is a legitimate job that involves labeling data such as images, text, or videos to train machine learning models. It requires attention to detail and familiarity with annotation tools, and it is widely used in AI development. The work is real and essential for creating accurate AI systems.

What is the difference between Data Annotation Services vs Data Labeling Specialists?

AspectData Annotation ServicesData Labeling Specialists
CredentialsTypically no formal credentials required; focus on trainingOften have training in specific tools or industry standards
Work EnvironmentCollaborative, often remote or in-office teamsSimilar, working in teams or independently on labeling tasks
Industry UsageUsed by AI/ML companies for training datasetsEmployed in similar settings, focusing on labeling data for AI models
Search & Comparison IntentUnderstanding services offered for data preparationLooking for roles or tasks related to data labeling

Data Annotation Services encompass the broader process of preparing and annotating data for AI and machine learning projects, often provided by specialized companies. Data Labeling Specialists are individual professionals or team members who perform the actual labeling tasks within these services. While both are closely related, services refer to the overall offering, whereas specialists are the personnel executing the work.

What are some common challenges faced when working in data annotation services, and how can I address them?

In data annotation services, one common challenge is maintaining consistency and accuracy, especially when handling large datasets or ambiguous data points. Clear annotation guidelines and regular communication with team leads help ensure that everyone interprets the data similarly. Additionally, repetitive tasks can lead to fatigue, so it's important to take scheduled breaks and leverage available annotation tools to streamline workflows. Collaborating with peers to discuss edge cases also helps improve overall data quality and fosters a supportive team environment.

What does a data annotation job do?

A data annotation job involves labeling or tagging data such as images, text, or videos to help train machine learning models. Workers use tools to add metadata, which improves the accuracy of AI systems, often working remotely with flexible schedules and requiring attention to detail. Knowledge of annotation tools and data quality standards is beneficial.

What are data annotation services?

Data annotation services involve labeling or tagging data—such as images, text, audio, or video—to make it understandable for machine learning models. These services are essential in training artificial intelligence systems to recognize patterns, objects, or other relevant information in raw data. Companies use data annotation to improve the accuracy and effectiveness of AI applications, such as self-driving cars, chatbots, and image recognition. Professional annotators or specialized platforms often perform these tasks to ensure high-quality, consistent results.
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Infographic showing various Data Annotation Services job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 88% Full Time, 7% Part Time, and 4% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution.
Python Developer _ MRM & Data Annotation (AI/ML)

Python Developer _ MRM & Data Annotation (AI/ML)

Tata Consultancy Services

Charlotte, NC • On-site

$49 - $67.75/hr

Full-time

Posted 17 days ago

Tata Consultancy Services rating

6.5

Company rating: 6.5 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

157th of 207 rated it services

Job description

Job Summary:
Tata Consultancy Services is seeking a Python Developer specializing in MRM and Data Annotation within the AI/ML domain. The role involves building and maintaining Python pipelines, implementing MRM controls, and collaborating with various teams to ensure model governance and data quality.
Responsibilities:
• 10+ years of hands experience in Python , MRM , Data Annotator
• Build and maintain Python pipelines for data ingestion, preprocessing, and model feature preparation.
• Implement MRM controls such as model documentation, versioning, validation evidence, and audit trails.
• Develop tools for annotation workflow automation (task assignment, QA sampling, and label consistency checks).
• Collaborate with risk, compliance, and data science teams to align model development with governance standards.
• Create reproducible training/evaluation scripts with clear experiment tracking and model lineage.
• Define and monitor model performance, drift, and data quality metrics across lifecycle stages.
• Design labeling guidelines and enforce annotation standards to improve downstream model reliability.
• Perform root-cause analysis for model errors and annotation defects, then drive corrective actions.
• Build APIs/utilities for secure data access, transformation, and integration with internal platforms.
• Support model validation activities with technical artifacts, assumptions, and testing evidence.
• Ensure adherence to data privacy, security, and responsible AI policies in all workflows.
• Document SOPs, handover notes, and technical runbooks for operational continuity.
Qualifications:
Required:
• Python
• MRM
• Data Annotator
• Agile concepts
• CI/CD
• 10+ years’ experience
• 10+ years of hands experience in Python, MRM, Data Annotator
• Build and maintain Python pipelines for data ingestion, preprocessing, and model feature preparation.
• Implement MRM controls such as model documentation, versioning, validation evidence, and audit trails.
• Develop tools for annotation workflow automation (task assignment, QA sampling, and label consistency checks).
• Collaborate with risk, compliance, and data science teams to align model development with governance standards.
• Create reproducible training/evaluation scripts with clear experiment tracking and model lineage.
• Define and monitor model performance, drift, and data quality metrics across lifecycle stages.
• Design labeling guidelines and enforce annotation standards to improve downstream model reliability.
• Perform root-cause analysis for model errors and annotation defects, then drive corrective actions.
• Build APIs/utilities for secure data access, transformation, and integration with internal platforms.
• Support model validation activities with technical artifacts, assumptions, and testing evidence.
• Ensure adherence to data privacy, security, and responsible AI policies in all workflows.
• Document SOPs, handover notes, and technical runbooks for operational continuity.
• Proactive and result-oriented leader, adept in mentoring and motivating the dynamic team to exemplary performance.
• Strong communication, collaboration, and team building skills with proficiency in grasping new technical concepts quickly
• BACHELOR OF COMPUTER SCIENCE
Company:
Tata Consultancy Services is a business solutions company that specializes on information technology services and consulting. It is a sub-organization of Tata Group. Founded in 1968, the company is headquartered in Mumbai, IND, with a team of 10001+ employees. The company is currently Late Stage.

What Tata Consultancy Services employees say

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Hours and flexibility

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About Tata Consultancy Services

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Tata Consultancy Services is an IT services, consulting and business solutions organization that delivers real results to global business, ensuring a level of certainty no other firm can match. TCS offers a consulting-led, integrated portfolio of IT, BPO, infrastructure, engineering, and assurance services. This is delivered through its unique Global Network Delivery Model™, recognized as the benchmark of excellence in software development. TCS delivers a level of certainty that no other firm can match--to our clients and to our employees. Come join us and experience certainty in your career. TCS a global Consulting and IT Services firm that is ranked in the top quartile by industry analysts. Our 2021 fiscal revenues topped $25 B and our market capitalization is over $170+B, yet we have a deep and large history of philanthropy and corporate social responsibility. Now approaching 600K of the best IT professionals and consultants, we are a trusted advisor, guiding our clients' enterprises through growth and transformation journeys - helping them to become agile, intelligent, automated and on the cloud. We are devoted to DEI and are recognized as a top employer and place to work.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Edison, NJ, US

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