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Platforms Similar To Data Annotation Tech Jobs (NOW HIRING)

Abaka AI is built on the mission to be the world's most trusted data partner for AI companies. The ... similar technologies • Experience supporting data annotation, AI training, data operations, or ...

Evaluate the performance of trained models to gauge their efficacy and readiness for deployment. Data Management and Annotation: * Design and develop test and training datasets as per the criteria ...

Data Labeling Associate

New York, NY

$17.50 - $22.75/hr

Evaluate the performance of trained models to gauge their efficacy and readiness for deployment. Data Management and Annotation: * Design and develop test and training datasets as per the criteria ...

Abaka AI is built on a mission to be the world's most trusted data partner for AI companies. The ... data platforms, crowdsourcing platforms, trust & safety organizations, or large-scale annotation ...

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How much do platforms similar to data annotation tech jobs pay per hour?

As of Jun 7, 2026, the average hourly pay for platforms similar to data annotation tech in the United States is $22.84, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $27.16 per hour, depending on experience, location, and employer.

What is the difference between Platforms Similar To Data Annotation Tech vs Data Labeling Specialist?

AspectPlatforms Similar To Data Annotation TechData Labeling Specialist
Required CredentialsBasic technical skills, familiarity with annotation toolsOften requires domain-specific knowledge and attention to detail
Work EnvironmentPrimarily remote or office-based, using annotation softwareSimilar, with focus on labeling data for AI/ML models
Employer & Industry UsageTech companies, AI startups, data service providersAI/ML companies, data firms, research institutions
Search & Comparison IntentUnderstanding roles similar to data annotation platformsClarifying differences between annotation tech platforms and labeling roles

Platforms Similar To Data Annotation Tech focus on providing tools and environments for data annotation, while Data Labeling Specialists perform the actual labeling work. Both roles are essential in AI data pipelines but differ in responsibilities and skill requirements.

Infographic showing various Platforms Similar To Data Annotation Tech job openings in the United States as of May 2026, with employment types broken down into 2% Locum Tenens, 94% Full Time, and 4% Part Time. Highlights an 46% Physical, 1% Hybrid, and 53% Remote job distribution, with an average salary of $47,512 per year, or $22.8 per hour.

Technical Project Associate

Abaka AI

Mountain View, CA • On-site

Full-time

Posted 5 days ago


Job description

Job Summary:
Abaka AI is built on the mission to be the world’s most trusted data partner for AI companies. The Technical Project Associate will help design, build, and scale operational systems for AI data annotation and quality control programs, focusing on automating workflows and improving operational efficiency.
Responsibilities:
• Design, build, improve, and maintain internal workflows, automation systems, and operational tooling for data annotation and quality control programs
• Develop scripts, integrations, and AI-assisted solutions that reduce manual work and improve operational efficiency
• Build and maintain dashboards, reporting systems, and data management workflows that improve visibility across projects
• Collaborate with Project Managers, Operations teams, Reviewers, and Leadership to identify bottlenecks and implement scalable solutions
• Monitor workflow performance, troubleshoot operational issues, and resolve data inconsistencies
• Leverage AI coding agents and AI-assisted development tools to rapidly prototype, test, and deploy process improvements
• Create systems that improve reviewer productivity, quality control accuracy, project tracking, and operational reporting
• Document internal tools, workflows, and best practices to support long-term scalability
• Proactively identify opportunities for automation and operational optimization instead of only executing predefined tasks
• Support cross-functional initiatives as Abaka AI continues to scale globally
Qualifications:
Required:
• Bachelor’s degree in Computer Science, Computer Engineering, Data Engineering, Information Systems, Industrial Engineering, or a related technical field
• Strong technical foundation in software development, automation, systems building, or operational tooling
• Experience improving business or operational processes through automation and tooling development: building projects, scripts, automations, or internal tools using Python or similar programming languages
• Familiarity with AI coding agents and AI-assisted development tools such as Claude Code, Codex, Cursor, GitHub Copilot, or similar platforms
• Understanding of APIs, workflow automation, system integrations, and structured data management concepts
• Familiarity with databases, data modeling, and operational data workflows
• Experience building or maintaining workflows using platforms such as Airtable, Retool, Zapier, n8n, Make, or similar tools
• Strong analytical thinking and problem-solving abilities
• Excellent communication and cross-functional collaboration skills
• Self-motivated, proactive, and comfortable operating in fast-paced, ambiguous environments
• Ability to quickly learn new tools, systems, and operational workflows
Preferred:
• Experience building workflow automation systems, internal operational tools, or reporting dashboards
• Familiarity with cloud infrastructure and developer tools such as AWS, GCP, Docker, Airflow, or similar technologies
• Experience supporting data annotation, AI training, data operations, or quality assurance workflows
• Previous experience as a reviewer, QA/QC specialist, trainer, or operations analyst
• Interest in AI, machine learning, and large-scale data infrastructure
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.