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Data Annotation Services Jobs (NOW HIRING)

Abaka AI

Data Operations Engineer

Mountain View, CA · On-site

$136K - $163K/yr

Abaka AI provides accurate and efficient AI data services, including data collection, data cleaning, data annotation, and OTS datasets. Founded in 2021, the company is headquartered in Palo Alto, USA ...

Abaka AI

Data Operations Engineer

Mountain View, CA · On-site

$136K - $163K/yr

Abaka AI provides accurate and efficient AI data services, including data collection, data cleaning, data annotation, and OTS datasets. Founded in 2021, the company is headquartered in Palo Alto, USA ...

Abaka AI

Data Operations Engineer

Mountain View, CA · On-site

$136K - $163K/yr

Abaka AI provides accurate and efficient AI data services, including data collection, data cleaning, data annotation, and OTS datasets. Founded in 2021, the company is headquartered in Palo Alto, USA ...

Pumpkin Intelligence, Inc.

Data Labeler

$30K - $50K/yr

Help improve evaluation guidelines and annotation processes * Contribute to the datasets used to ... All the hardware, tools, and services you need How We Hire * Intro call with HR (25 min) * Take ...

Grid Dynamics Holdings

Technical Project Manager

Own the planning, scheduling, execution, and delivery of high-volume data annotation projects ... Define, monitor, and enforce service-level agreements (SLAs) and key performance indicators (KPIs ...

Abaka AI

Data Solutions Engineer

Mountain View, CA · On-site

$136K - $163K/yr

Abaka AI provides accurate and efficient AI data services, including data collection, data cleaning, data annotation, and OTS datasets. Founded in 2021, the company is headquartered in Palo Alto, USA ...

Abaka AI

Data Solutions Engineer

Mountain View, CA · On-site

$136K - $163K/yr

Abaka AI provides accurate and efficient AI data services, including data collection, data cleaning, data annotation, and OTS datasets. Founded in 2021, the company is headquartered in Palo Alto, USA ...

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Data Annotation Services information

What are the key skills and qualifications needed to thrive in data annotation services?

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.

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 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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Data Annotation Services jobs near you
Infographic showing various Data Annotation Services job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 16% Part Time, 1% Temporary, and 4% Contract. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution.

Data Operations Engineer

Abaka AI

Mountain View, CA • On-site

$136K - $163K/yr

Full-time

Re-posted 25 days ago

Job description

Job Summary:
Abaka AI is built on one mission: to be the world’s most trusted data partner for AI companies. They are seeking a Data Operations Engineer to own and operate the internal dataset library, ensuring fast, accurate, and scalable access to data while coordinating with engineering, product, and business teams.
Responsibilities:
• Develop and maintain a comprehensive understanding of Abaka AI’s dataset library, including data structure, quality, and applicable use cases across modalities (text, image, video, audio, 3D).
• Serve as the internal point of contact for dataset-related inquiries, providing clear and timely responses to questions from engineering, product, and business teams.
• Translate ambiguous or high-level requests into concrete dataset solutions, identifying appropriate data sources or gaps.
• Inspect and validate datasets for quality, completeness, and consistency using SQL, Python, or other tools as needed.
• Coordinate with global data teams, including teams in China, to resolve data issues, clarify requirements, and ensure timely delivery without unnecessary escalation.
• Maintain and improve internal documentation, organization, and accessibility of datasets.
• Identify inefficiencies in current workflows and propose improvements to systems, tooling, and processes that support dataset management and usage.
• Support cross-functional initiatives by providing dataset insights, technical context, and operational guidance.
Qualifications:
Required:
• Bachelor’s degree in Computer Science, Data Engineering, or a related field, or equivalent practical experience.
• 1–4 years of experience in data operations, data engineering, or a related role involving direct interaction with datasets.
• Professional proficiency in Mandarin Chinese and English is required, as this role involves frequent collaboration with China-based vendors and external partners.
• Strong problem-solving skills and ability to operate effectively in ambiguous, fast-paced environments.
• Proficiency in SQL and/or Python for data inspection, validation, and basic analysis.
• Experience working with real-world datasets, including handling data quality issues, inconsistencies, and edge cases.
• Strong communication skills, with the ability to work across technical and non-technical teams.
• High level of ownership and accountability, with the ability to manage multiple requests and priorities simultaneously.
Preferred:
• Experience with multimodal datasets (text, image, video, audio, or 3D).
• Familiarity with data annotation, labeling workflows, or dataset preparation for machine learning.
• Experience working with international teams, particularly in cross-border environments.
• Exposure to AI/ML workflows, including training, fine-tuning, or evaluation datasets.
Company:
Abaka AI provides accurate and efficient AI data services, including data collection, data cleaning, data annotation, and OTS datasets. Founded in 2021, the company is headquartered in Palo Alto, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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