ZipRecruiter

Log In

1

Per Diem Ai Data Annotation Jobs (NOW HIRING)

Abaka AI

Quality Project Associate

Responsibilities : • Build and improve quality assurance and compliance systems across AI data annotation projects • Design quality standards, review processes, escalation workflows, and ...

Abaka AI

Technical Project Associate

Mountain View, CA · On-site

Abaka AI is committed to being the world's most trusted data partner for AI companies. The Technical Project Associate will design, build, and scale operational systems for AI data annotation and ...

Abaka AI

Technical Project Associate

Mountain View, CA · On-site

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 ...

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 ...

next page

Showing results 1-20

All JobsPer Diem Ai Data Annotation Jobs

Per Diem Ai Data Annotation information

See salary details

$37.5K

$122.7K

$196.5K

How much do per diem ai data annotation jobs pay per year?

As of Jun 10, 2026, the average yearly pay for per diem ai data annotation in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is the difference between Per Diem Ai Data Annotation vs Data Labeler?

AspectPer Diem Ai Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote or on-site, flexible hours
Industry UsageAI, machine learning, tech companiesAI, machine learning, tech companies
Job FocusAnnotating data for AI training, often on a per-project basisLabeling data to improve AI models, often on a per-task basis

Both roles involve data annotation and are used in AI and machine learning industries. Per Diem Ai Data Annotation typically refers to short-term, project-based work with flexible schedules, while Data Labelers may work on similar tasks but often with a broader scope or different employment arrangements. Both require attention to detail and basic technical skills, making them closely related roles in the data annotation field.

What is a Per Diem AI Data Annotation job?

A Per Diem AI Data Annotation job involves labeling, tagging, or categorizing data—such as images, text, or audio—on a flexible, as-needed basis to help train artificial intelligence and machine learning models. 'Per diem' means the position is paid by the day or for specific tasks, rather than being a full-time or salaried role. These jobs are vital for ensuring AI systems learn from accurate, well-labeled datasets. The work is often remote and may vary in workload based on project needs. Attention to detail and consistency are important qualities for success in this role.

What are some common challenges faced by Per Diem AI Data Annotation professionals, and how can they be addressed?

Per Diem AI Data Annotation professionals often encounter challenges such as maintaining consistency in labeling, meeting tight deadlines, and adapting to evolving project guidelines. It is important to carefully review annotation instructions and ask clarifying questions when uncertainties arise. Staying organized and regularly communicating with team leads or project managers can help address ambiguities and ensure high-quality, accurate annotations. Additionally, leveraging available training resources and collaborating with peers can aid in staying up-to-date with best practices.

What are the key skills and qualifications needed to thrive as a Per Diem AI Data Annotation Specialist, and why are they important?

To thrive as a Per Diem AI Data Annotation Specialist, you need strong attention to detail, good analytical skills, and familiarity with data labeling concepts, often supported by a high school diploma or higher education in a related field. Familiarity with annotation platforms, data management systems, and sometimes basic programming or scripting tools is beneficial. Reliability, time management, and clear communication are key soft skills for meeting project deadlines and collaborating with remote teams. These skills ensure the accuracy and consistency of labeled data, which is critical for training high-performing AI models.
More about Per Diem Ai Data Annotation jobs
What cities are hiring for Per Diem Ai Data Annotation jobs? Cities with the most Per Diem Ai Data Annotation job openings:
What are the most commonly searched types of Ai Data Annotation jobs? The most popular types of Ai Data Annotation jobs are:
What states have the most Per Diem Ai Data Annotation jobs? States with the most job openings for Per Diem Ai Data Annotation jobs include:
What job categories do people searching Per Diem Ai Data Annotation jobs look for? The top searched job categories for Per Diem Ai Data Annotation jobs are:
Per Diem Ai Data Annotation jobs near you

Quality Project Associate

Abaka AI

Remote

Full-time

Posted 8 days ago

Job description

Job Summary:
Abaka AI is a trusted data partner for AI companies, focusing on providing scalable data solutions. The Quality Project Associate will build and scale quality systems for AI data operations, working closely with various teams to improve data quality and compliance in large-scale annotation programs.
Responsibilities:
• Build and improve quality assurance and compliance systems across AI data annotation projects
• Design quality standards, review processes, escalation workflows, and operational governance frameworks
• Develop quality metrics, auditing methodologies, reviewer calibration programs, and random inspection systems
• Monitor quality risks across large-scale annotator and reviewer pipelines
• Identify and mitigate fraud, abuse, and quality risks, including multi-accounting, VPN/proxy usage, AI-generated responses, and low-quality contributors
• Investigate root causes behind quality issues such as declining acceptance rates, reviewer misalignment, annotation quality degradation, workflow inefficiencies, and client requirement mismatches
• Develop corrective actions and scalable solutions that improve project quality and customer acceptance rates
• Improve reviewer consistency, accountability, and operational traceability across projects
• Collaborate cross-functionally with Project Managers, Operations, Product, QA teams, and Leadership to drive quality initiatives
• Support the development of scalable systems and processes that improve quality outcomes without increasing operational overhead
• Contribute to 0→1 initiatives that strengthen quality management and operational excellence across the organization
Qualifications:
Required:
• Strong operational foundation in quality assurance, crowdsourcing operations, trust & safety, compliance operations, project operations, or related fields
• Experience identifying and solving operational problems through process design, governance frameworks, or quality systems
• Strong analytical thinking and root cause analysis capabilities
• Understanding of crowdsourcing challenges such as reviewer inconsistency, contributor quality management, fraud prevention, and operational scalability
• Ability to design scalable, traceable, and repeatable operational processes
• High ownership mindset with the ability to operate independently in ambiguous environments
• Strong written and verbal communication skills
• Excellent stakeholder management and cross-functional collaboration abilities
• Detail-oriented with a commitment to operational excellence
• Interest in AI, machine learning, and large-scale data operations
• Growth-oriented mindset with a bias toward continuous improvement and execution
Preferred:
• Experience working at AI data platforms, crowdsourcing platforms, trust & safety organizations, or large-scale annotation operations
• Experience managing reviewers, contributors, quality programs, or operational teams
• Familiarity with quality dashboards, QA tooling, workflow management systems, or operational reporting platforms
• Experience improving acceptance rates, quality metrics, or operational performance at scale
• Startup or high-growth environment experience
• Experience building quality systems and governance frameworks from 0→1
• Familiarity with AI, LLM, data annotation, or human-in-the-loop workflows
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.

Apply