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Part Time Ai Rater Jobs (NOW HIRING)

Conflux Systems

Java AI Architect

Texarkana, TX · On-site

$70/hr

Inform the candidate that they must not have any other part-time or full-time employment while ... Rate: $70/hr. * Location: Remote * Duration: 6 months * See below: Must Have Technical/Functional ...

TestPros

Senior AI Test Engineer (Remote)

Sterling, VA · On-site +1

$50 - $80/hr

Start: Future projects in late 2026 or 2027 (not an immediate job opening) Type: Part-time ... Rate: $50-80/hr. 1099 or Corp. To Corp.). This range represents a good-faith estimate and is not a ...

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Part Time Ai Rater information

What is a part time AI rater?

Part-time AI raters are individuals who work remotely to evaluate and provide feedback on the performance of artificial intelligence systems, such as search engines or virtual assistants. They follow specific guidelines to rate the relevance and accuracy of results produced by AI algorithms, helping to improve the quality and reliability of these systems. Typically, this role offers flexible hours and does not require advanced technical skills, but attention to detail and good communication skills are important. Part-time AI raters often work for companies that develop or use AI-powered products and services.

What are the key skills and qualifications needed to thrive as a part time AI rater?

To thrive as a Part Time AI Rater, you need strong analytical skills, attention to detail, and proficiency in written English, often supported by at least a high school diploma or equivalent. Familiarity with web browsers, online research tools, and proprietary rating platforms is typically required, and some employers may require passing an initial qualification exam. Effective time management, reliability, and the ability to follow detailed guidelines are critical soft skills for this remote role. These skills ensure consistent, high-quality data labeling and feedback, which are essential for improving AI systems' accuracy and relevance.

What are some common challenges faced by part time AI raters, and how can they be addressed?

Part-time AI raters often encounter challenges such as maintaining consistency in their evaluations, understanding complex guidelines, and managing repetitive tasks. To address these, it's important to thoroughly review training materials, ask clarifying questions when unsure, and take regular breaks to maintain focus. Effective communication with team leads and participating in feedback sessions can also help improve accuracy and efficiency in the role.

What is the difference between Part Time Ai Rater vs Part Time Content Moderator?

AspectPart Time Ai RaterPart Time Content Moderator
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentOnline, remoteOnline, remote or on-site
Industry UsageTech companies, AI developmentSocial media, online platforms
Job FocusEvaluating AI outputs for accuracyMonitoring and moderating user-generated content

Part Time Ai Raters primarily evaluate AI responses to improve machine learning models, focusing on AI output accuracy. In contrast, Part Time Content Moderators review user-generated content to ensure community guidelines are followed. While both roles are remote and require similar skills, their main responsibilities and industry applications differ.

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What are the most commonly searched types of Ai Rater jobs?

The most popular types of Ai Rater jobs are:

What job categories do people searching Part Time Ai Rater jobs look for?

The top searched job categories for Part Time Ai Rater jobs are:

Part Time Ai Rater jobs near you
Infographic showing various Part Time Ai Rater job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 21% Part Time, and 3% Contract. Highlights an 64% Physical, 4% Hybrid, and 32% Remote job distribution.

Java AI Architect

Conflux Systems

Texarkana, TX • On-site

$70/hr

Full-time, Part-time

Posted 8 days ago

Job description

Visa not allowed.
  • CPT EAD
  • Stem - OPT
  • OPT EAD
  • FTE to Subco conversion - 6 months cooling period we need to follow or get approval.

  • Atos has stringent compliance and security requirements that all employees are expected to adhere to.
  • Inform the candidate that they must not have any other part-time or full-time employment while working with Atos on this assignment.
  • Obtain explicit confirmation from the candidate that they understand and are comfortable with these requirements and the expected work arrangement before proceeding further.

  • Client Name: Digital Practice - Internal Customer
  • Posman ID: POSMAN_127590
  • Position ID: 30390692
  • Job Posting ID: ATGTJP00102507
  • Role/Skills: Java EE, React JS, MSGithub Copilot
  • Rate: $70/hr.
  • Location: Remote
  • Duration: 6 months
  • Job Description: See below:

Must Have Technical/Functional Skills:
• Proven experience as an AI Architect defining enterprise AI architecture, standards, and governance.
• Hands-on experience designing/building agent-based approaches and autonomous workflows.
• Strong expertise in Prompt Engineering (Zero/Few-shot, Chain-of-Thought) and prompt design.
• Strong Python development experience and ability to guide teams with reference implementations.
• Experience with RAG, vector databases, and cloud deployments.
• Practical experience with GitHub Copilot adoption patterns including guardrails, prompt library management, extensions, and metrics
Preferred / Nice to Have
• Experience designing enterprise adoption frameworks for Copilot/AI with change management and champion models.
• Experience building Copilot-led accelerators for engineering productivity and rapid prototyping.
• Knowledge of AI governance requirements and productionization practices.
Roles & Responsibilities
1) Architecture & Strategy (AI / Agentic AI)
• Define the overall solution architecture for enterprise agentic AI programs and create the target-state roadmap
• Establish AI architecture standards, reference patterns, and governance guidelines for adoption at scale.
• Design architecture across LLMs/frameworks, vector databases, and cloud deployments, including Responsible AI practices.
2) Autonomous Agent Design & Orchestration (Copilot-led)
• Architect and enable autonomous agent workflows using GitHub Copilot, including multi-step orchestration and enterprise guardrails.
• Define a framework for prompt libraries, guardrails, extensions/integrations, and productivity metric tracking for Copilot adopt
• Drive repeatable implementation approach and best practices for Copilot-based engineering interventions and productivity tracking
• Enable Copilot-driven acceleration from design artifacts (e.g., Figma requirement sheets) to boilerplate code and supporting assets, where applicable.
• Establish patterns for agent-assisted testing and a roadmap toward autonomous testing where feasible (e.g., test case generation, script automation, regression maintenance).
3) Prompt Engineering Excellence
• Own enterprise prompt strategy including Zero-shot / Few-shot / Chain-of-Thought prompting techniques and prompt governance.
• Create reusable prompt frameworks/cookbooks, templates, and standards for consistent outcomes across teams.
4) RAG + Model/Tool Orchestration (Python-led)
• Architect and govern RAG pipelines, knowledge grounding approaches, and multi-turn agent orchestration using frameworks such as LangChain (or equivalent).
• Provide hands-on guidance for implementation in Python, including reference implementations and integration patterns.

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