Full-time Remote Quality Controller Jobs in Saudi Arabia

About the Role

YO IT Consulting is seeking a Data Scientist Quality Assurance Lead for a contract, hourly role. This position focuses on overseeing quality, consistency, and trainer performance within data science AI training projects. The role is with a rapidly growing AI Data Services company that provides training data for major AI companies and foundation-model labs. Your expertise in data science quality will be crucial in ensuring that training data is analytically sound, reproducible, clearly documented, and aligned with client expectations.

Role Overview and Responsibilities

In this remote contractor position, you will be responsible for a range of quality assurance tasks related to data science AI training content. This includes:

• Reviewing AI-generated data science content and the work of trainers and QA personnel.
• Evaluating output quality against established project guidelines and rubrics.
• Providing precise, written feedback to contributors.
• Ensuring all contributors adhere to expected quality standards.
• Assessing work for statistical accuracy, data reasoning, model selection quality, code correctness, reproducibility, metric interpretation, business context awareness, clarity, formatting, instruction adherence, and alignment with project-specific rubrics.
• Identifying recurring quality issues and communicating updates to trainers and QAs.
• Supporting the onboarding process for new contributors.
• Maintaining relevant documentation.
• Assisting in activating contributors who are not working consistently.
• Performing technical reviews of AI-generated data science explanations, code snippets (Python/R/SQL), modeling workflows, statistical interpretations, dashboards, experiment designs, and step-by-step reasoning.
• Handling questions related to statistical assumptions, metrics, model selection, data leakage, validation, coding choices, reproducibility, and rubric interpretation.
• Managing trainer/QA activation by encouraging engagement, tracking follow-ups, and flagging availability issues.
• Reviewing data science outputs for potential risks such as misleading or statistically invalid conclusions.
• Contributing to process improvement by identifying quality gaps and helping to build scalable QA processes.

Qualifications and Experience

Candidates for this role should possess the following qualifications:

• A Bachelor’s, Master’s, or PhD degree in Data Science, Statistics, Computer Science, Machine Learning, Mathematics, Economics, Engineering, or a closely related quantitative field.
• A minimum of 2-5 years of professional experience in data science, analytics, machine learning, statistical modeling, experimentation, data engineering, technical review, or data science education.
• A strong understanding of statistics, probability, data cleaning, exploratory data analysis, feature engineering, supervised/unsupervised learning, model evaluation, experimentation, regression, classification, clustering, and validation methods.
• The ability to evaluate data science content against detailed rubrics and identify issues such as data leakage, flawed assumptions, incorrect metrics, weak methodology, non-reproducible code, or misleading conclusions.
• Proficiency in English, enabling clear communication and the ability to provide detailed technical feedback.
• Experience leading or supporting remote teams of trainers, annotators, analysts, data scientists, engineers, educators, or QAs is strongly preferred.
• Experience with AI training, data annotation, LLM evaluation, data science QA, or rubric-based technical review is a strong plus.

Technical Skills and Tools

Familiarity with the following tools and platforms is preferred:

• Programming languages and libraries such as Python (pandas, NumPy, scikit-learn), R, and SQL.
• Development environments and tools including Jupyter, Git, and MLflow.
• Data visualization tools like matplotlib and dashboarding platforms.
• Big data technologies such as Spark.
• Cloud platforms and general data platforms.
• Collaboration and project management tools including Discord, Google Sheets, Google Docs, trackers, dashboards, GitHub, and project management systems.

Work Arrangement and Application Process

This is a remote, contract-based hourly position. The selection process involves an AI interview, a domain-specific task, and an interview with a recruiter. While there is no immediate project assignment for this role, qualified candidates will be prioritized for future relevant opportunities and gain access to YO IT Consulting's expert network.

About the Role

YO IT Consulting is seeking a skilled JavaScript Quality Assurance Lead for a full-time contract position. This role is fully remote. In this capacity, you will be responsible for overseeing the quality and consistency of JavaScript AI training projects. Your duties will involve meticulously reviewing AI-generated JavaScript code and the work of trainers and QA personnel, evaluating output against project guidelines, and ensuring adherence to stringent quality standards. This includes assessing code correctness, reasoning quality, runtime behavior, debugging accuracy, readability, maintainability, performance, security awareness, test coverage, formatting, instruction adherence, and compliance with project-specific rubrics.

This is an opportunity to contribute to an AI Data Services company that partners with leading AI companies and foundation-model labs. Your expertise in JavaScript quality leadership will directly enhance the accuracy, executability, logical soundness, clarity, documentation, and overall alignment of JavaScript training data with client expectations, thereby improving AI models. The selection process includes an AI interview, a domain-specific task, and an interview with a recruiter. Qualified candidates will be prioritized for future opportunities and gain access to an expert network.

Key Responsibilities

• Conduct quality monitoring by spot-checking JavaScript items, identifying quality issues, providing ongoing feedback through direct messages, and escalating recurring or critical issues.
• Perform code reviews, evaluating AI-generated JavaScript code, debugging responses, implementation explanations, algorithmic solutions, frontend/backend snippets, tests, and step-by-step reasoning for correctness and clarity.
• Communicate updates to trainers and QAs via Discord regarding new item guidelines, project changes, workflow updates, quality expectations, and JavaScript-specific review standards.
• Respond clearly and promptly to trainer/QA questions, particularly concerning JavaScript behavior, asynchronous logic, browser vs. **** environments, frameworks, package usage, testing, edge cases, and rubric interpretation.
• Manage trainer/QA activation by messaging inactive or underperforming contributors, encouraging engagement, tracking follow-ups, and flagging availability issues when necessary.
• Create and maintain comprehensive JavaScript project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
• Schedule and conduct onboarding and training sessions for trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and JavaScript-specific review requirements.
• Ensure consistent application of JavaScript review guidelines by all trainers and QAs, and effectively communicate updates as projects evolve.
• Flag unsafe, misleading, insecure, or overconfident code recommendations, with a particular focus on injection risks, dependency usage, authentication, browser security, data handling, and production readiness.
• Identify recurring quality gaps, propose workflow improvements, and contribute to building scalable QA processes for JavaScript AI training projects.

Qualifications and Requirements

• Bachelor's or Master's degree in Computer Science, Software Engineering, Information Technology, or a closely related field. Equivalent professional software engineering experience will also be considered.
• Strong English language proficiency to effectively follow project guidelines, communicate with teams, and provide clear technical feedback.
• 3+ years of professional experience in JavaScript development, frontend engineering, backend development with ****, full-stack engineering, code review, software QA, technical mentoring, or related workflows.
• A strong understanding of core JavaScript concepts, including closures, scope, hoisting, prototypes, promises, async/await, the event loop, modules, DOM manipulation, error handling, data structures, and modern ECMAScript features.
• Capability to evaluate JavaScript content against detailed rubrics and identify issues such as incorrect logic, non-executable code, flawed reasoning, missing edge cases, poor asynchronous handling, security risks, performance problems, hallucinated APIs, or incomplete explanations.
• Experience leading or supporting remote teams of trainers, annotators, reviewers, engineers, technical writers, coding mentors, or QAs is strongly preferred.
• Comfort working in fast-moving remote environments utilizing tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, GitHub, and project management systems.
• Exceptional attention to detail and organizational skills, with the ability to maintain style guides, FAQs, trackers, onboarding materials, honeypots, and calibration tasks.
• Experience with AI training, data annotation, large language models, prompt/response evaluation, code content QA, or rubric-based LLM evaluation is a strong plus.

Technical Skills

• JavaScript
• Quality Assurance
• Communication
• Attention to Detail
• ****
• React
• Vue
• Express
• Jest
• Mocha
• Playwright
• ESLint
• Prettier
• Vite
• Webpack
• Babel
• Browser Developer Tools
• AI Training Data
• Data Annotation
• Large Language Models
• Prompt/Response Evaluation
• Code Content QA
• Rubric-based LLM Evaluation
• Familiarity with common JavaScript ecosystems and tools such as npm/yarn/pnpm is preferred.

Work Environment and Contract Details

This is a full-time contract position. The role is entirely remote, allowing you to work from any location. The company is YO IT Consulting. While specific project assignments are not immediate, qualified candidates will be considered for future opportunities. The company operates in the AI Data Services sector, collaborating with major AI companies and foundation-model labs globally. The required experience for this role is 2-5 years.

About the Role

Jobgether is seeking a QA Automation Engineer on behalf of a partner company located in Saudi Arabia. This role is essential for ensuring the quality and reliability of mobile-driven notification systems. The position involves executing structured testing and simulating real-world usage scenarios, with a focus on modern mobile applications, particularly on Android devices. The role requires accuracy, meticulous attention to detail, and consistent daily execution of test workflows.

This is a fully remote, project-based engagement designed for professionals experienced in mobile-first testing. You will work with notification-heavy environments to validate sorting, behavior tracking, and system responsiveness. The role offers exposure to experimental AI-driven product development and emerging mobile technologies. This is a short-term opportunity with potential for future assignments based on performance.

Key Responsibilities

• Execute structured QA testing workflows focused on mobile notification systems and app behavior validation.
• Utilize Android-based devices, specifically Google Pixel 9 or newer models, to simulate real-world user interactions and test notification handling.
• Perform daily test activities, including notification sorting, organization, and detailed documentation of observed behavior.
• Submit consistent daily QA reports and feedback forms to support tracking and product improvement initiatives.
• Identify, document, and escalate technical issues or inconsistencies encountered during testing phases.
• Adhere strictly to detailed test instructions, ensuring high accuracy, completeness, and compliance with established QA standards.
• Maintain strict confidentiality and adhere to all project guidelines throughout the engagement period.

Qualifications and Requirements

• Native or expert-level proficiency in American English (en_us).
• Demonstrated experience or strong familiarity with QA testing, mobile application testing, or structured task execution environments.
• Must own and actively use a qualifying Google Pixel device (Pixel 9 or newer models).
• Comfortable installing and using mobile applications that generate frequent notifications.
• Ability to perform consistent daily tasks for a period of 14 consecutive days, with a daily time commitment of 10-15 minutes.
• Possess a reliable internet connection and exhibit strong attention to detail.
• Willingness to complete a language and/or task-based assessment as part of the application process.
• Capability to follow structured instructions precisely and maintain high-quality output within a remote work setup.

Required Skills

• QA testing
• Mobile application testing
• Structured task execution
• Notification systems analysis
• Attention to detail
• Documentation and reporting

Project Details and Compensation

This is a project-based engagement for a partner company in Saudi Arabia. The work is fully remote and requires a minimal daily time commitment of 10-15 minutes for 14 consecutive days. Upon successful completion of the 14-day testing period, a one-time payment of USD $225 will be provided. Jobgether utilizes an AI-powered matching process for candidate review, and shortlisted candidates will be shared directly with the hiring company for further steps, including interviews and assessments.

About the Role

DataAnnotation is seeking a bilingual Customer Support Specialist to join their team. In this role, you will contribute to training and improving advanced AI models by evaluating chatbot performance, measuring their progress, assessing their logic, and identifying and resolving issues to enhance model quality.

Role Responsibilities

• Engage in conversations in both Arabic and English with chatbots to evaluate their performance and measure their progress.
• Write new conversational content and provide feedback to train AI models on appropriate responses and interactions.
• Assign writing and editing tasks to chatbots and accurately assess the quality of their output.
• Evaluate the overall accuracy and performance of AI models, providing detailed feedback for improvement.

Qualifications and Requirements

• Fluency in both Arabic and English is essential for this role.
• Must possess a detail-oriented approach to tasks and evaluations.
• Excellent understanding of grammar, style, and the ability to adhere to brand tone guidelines.
• A current, in-progress, or completed Bachelor's degree is preferred but not mandatory.

Skills Required

• Advanced knowledge of linguistics.
• Strong problem-solving abilities.
• Exceptional attention to detail.
• Proficiency in grammar and style.
• Understanding of brand tone principles.

Job Details and Compensation

This position is an independent contract. The role requires 5-10 years of experience. Compensation is offered at $25 USD per hour, with the potential for additional rates for selected projects. Payments are processed via PayPal, which will handle any necessary currency conversions from USD. DataAnnotation will never ask for money from contractors.

Work Environment and Flexibility

The work location is in Saudi Arabia. This role offers flexibility as you can choose projects and set your own work schedule, working from your computer in your home. This position is a full-time independent contract.

About the Role

YO IT Consulting is seeking a Geology Quality Assurance Lead for a remote, contract position. This role is critical for overseeing the quality, consistency, and performance of AI training projects focused on geology and earth sciences. The successful candidate will contribute to the accuracy and contextualization of training data used by leading AI companies and foundation-model labs, directly impacting the improvement of premier AI models.

Role Overview and Responsibilities

In this role, you will be responsible for ensuring the high quality of AI-generated earth science and geology content. This involves reviewing AI outputs and the work of trainers and QA personnel against project guidelines. You will provide precise written feedback to contributors, assessing work for scientific accuracy, geologic reasoning, terminology, spatial and temporal context, data interpretation, clarity, formatting, and adherence to project-specific rubrics. Key responsibilities include:

• Evaluating AI-generated content and trainer/QA work for quality and adherence to guidelines.
• Providing detailed written feedback to ensure contributors meet expected quality standards.
• Assessing work for scientific accuracy, geologic reasoning, terminology, context, data interpretation, clarity, and rubric compliance.
• Spot-checking geology and earth science items, identifying quality issues, and delivering ongoing feedback.
• Escalating recurring or critical quality issues.
• Evaluating AI-generated explanations, summaries, process descriptions, and interpretations for accuracy and clarity.
• Flagging any misleading, geologically impossible, unsupported, or poorly contextualized earth science claims.

Communication and Support

Effective communication is essential for this role. You will be responsible for:

• Communicating project updates, new guidelines, workflow changes, and quality expectations to trainers and QAs via platforms like Discord.
• Promptly responding to questions from trainers and QAs, particularly concerning geological concepts and rubric interpretation.
• Supporting the onboarding of new contributors.
• Monitoring contributor activity, encouraging engagement, and flagging availability issues when necessary.

Documentation and Process Improvement

This role involves maintaining and improving project documentation and processes:

• Creating and maintaining project documentation, including style guides, trackers, FAQs, quality notes, and onboarding materials.
• Identifying recurring quality issues and proposing workflow enhancements.
• Assisting in the development of scalable QA processes for earth science and geology AI training projects.

Qualifications and Experience

Candidates should possess the following qualifications:

• A Bachelor’s, Master’s, or PhD degree in Geology, Earth Sciences, Geoscience, Environmental Science, Geophysics, Geochemistry, Hydrology, Paleontology, Oceanography, or a closely related field.
• A minimum of 2-5 years of experience in geology/earth science research, teaching, fieldwork, environmental consulting, geospatial analysis, academic review, science communication, or related areas.
• Experience leading or supporting remote teams of researchers, educators, reviewers, or QAs is strongly preferred.
• Experience with AI training, data annotation, LLM evaluation, scientific QA, or rubric-based review is a significant advantage.

Skills and Knowledge

Required skills and knowledge include:

• Strong command of the English language for clear communication and feedback.
• A solid understanding of core geological concepts including plate tectonics, the rock cycle, mineralogy, stratigraphy, geologic time, structural geology, geomorphology, natural hazards, climate systems, hydrology, and earth system processes.
• The ability to critically evaluate earth science content against detailed rubrics and identify specific types of errors.
• Exceptional attention to detail and organizational skills.
• Comfort working in fast-paced remote environments using tools such as Discord, Google Sheets, Google Docs, and project management systems.
• Familiarity with tools or methods such as GIS, remote sensing, geologic mapping, field methods, core/log interpretation, geochemical data, climate datasets, Python/R, or scientific visualization is preferred.

The selection process includes an AI interview, a domain-specific task, and an interview with a recruiter. While there is no immediate project for this role, qualified candidates will be prioritized for future relevant opportunities and gain access to YO IT Consulting's expert network.

About the Role

YO IT Consulting is seeking a Geology Quality Assurance Lead for a remote, contract position. This role is critical for overseeing the quality, consistency, and performance of AI training projects focused on geology and earth sciences. The successful candidate will contribute to the accuracy and contextualization of training data used by leading AI companies and foundation-model labs, directly impacting the improvement of premier AI models.

Role Overview and Responsibilities

In this role, you will be responsible for ensuring the high quality of AI-generated earth science and geology content. This involves reviewing AI outputs and the work of trainers and QA personnel against project guidelines. You will provide precise written feedback to contributors, assessing work for scientific accuracy, geologic reasoning, terminology, spatial and temporal context, data interpretation, clarity, formatting, and adherence to project-specific rubrics. Key responsibilities include:

• Evaluating AI-generated content and trainer/QA work for quality and adherence to guidelines.
• Providing detailed written feedback to ensure contributors meet expected quality standards.
• Assessing work for scientific accuracy, geologic reasoning, terminology, context, data interpretation, clarity, and rubric compliance.
• Spot-checking geology and earth science items, identifying quality issues, and delivering ongoing feedback.
• Escalating recurring or critical quality issues.
• Evaluating AI-generated explanations, summaries, process descriptions, and interpretations for accuracy and clarity.
• Flagging any misleading, geologically impossible, unsupported, or poorly contextualized earth science claims.

Communication and Support

Effective communication is essential for this role. You will be responsible for:

• Communicating project updates, new guidelines, workflow changes, and quality expectations to trainers and QAs via platforms like Discord.
• Promptly responding to questions from trainers and QAs, particularly concerning geological concepts and rubric interpretation.
• Supporting the onboarding of new contributors.
• Monitoring contributor activity, encouraging engagement, and flagging availability issues when necessary.

Documentation and Process Improvement

This role involves maintaining and improving project documentation and processes:

• Creating and maintaining project documentation, including style guides, trackers, FAQs, quality notes, and onboarding materials.
• Identifying recurring quality issues and proposing workflow enhancements.
• Assisting in the development of scalable QA processes for earth science and geology AI training projects.

Qualifications and Experience

Candidates should possess the following qualifications:

• A Bachelor’s, Master’s, or PhD degree in Geology, Earth Sciences, Geoscience, Environmental Science, Geophysics, Geochemistry, Hydrology, Paleontology, Oceanography, or a closely related field.
• A minimum of 2-5 years of experience in geology/earth science research, teaching, fieldwork, environmental consulting, geospatial analysis, academic review, science communication, or related areas.
• Experience leading or supporting remote teams of researchers, educators, reviewers, or QAs is strongly preferred.
• Experience with AI training, data annotation, LLM evaluation, scientific QA, or rubric-based review is a significant advantage.

Skills and Knowledge

Required skills and knowledge include:

• Strong command of the English language for clear communication and feedback.
• A solid understanding of core geological concepts including plate tectonics, the rock cycle, mineralogy, stratigraphy, geologic time, structural geology, geomorphology, natural hazards, climate systems, hydrology, and earth system processes.
• The ability to critically evaluate earth science content against detailed rubrics and identify specific types of errors.
• Exceptional attention to detail and organizational skills.
• Comfort working in fast-paced remote environments using tools such as Discord, Google Sheets, Google Docs, and project management systems.
• Familiarity with tools or methods such as GIS, remote sensing, geologic mapping, field methods, core/log interpretation, geochemical data, climate datasets, Python/R, or scientific visualization is preferred.

The selection process includes an AI interview, a domain-specific task, and an interview with a recruiter. While there is no immediate project for this role, qualified candidates will be prioritized for future relevant opportunities and gain access to YO IT Consulting's expert network.

About the Role

RecruitLyticx Hires is looking for a remote Information Entry and Support Specialist to join their team. This is a full-time role, based in Medina, Saudi Arabia, and is essential for maintaining the accuracy and efficiency of our data processing operations. You will play a vital role in ensuring our systems are up-to-date and well-organized, supporting informed decision-making and effective business operations.

This role is ideal for an individual who values integrity, accuracy, and a strong commitment to quality. You will be responsible for more than just standard data entry, as you will contribute to information gathering, prioritization, quality control, and process improvement. The position offers a path for growth for those looking to advance beyond pure data entry into areas such as data management, quality assurance, or operations coordination.

Key Tasks and Responsibilities

• Perform data entry, updates, and maintenance of essential information across various organizational systems with a high degree of accuracy and consistency.
• Coordinate information gathering from various stakeholders.
• Prioritize data processing tasks based on urgency and business needs.
• Monitor data quality metrics and report on identified trends.
• Assist in training new team members on data entry standards and best practices.
• Contribute to the documentation of best practices and data entry procedures.
• Identify automation opportunities to improve data processing efficiency.
• Liaise between the data entry team and requesting departments to ensure clear communication and timely delivery of information.
• Resolve data conflicts or ambiguities through thorough research and consultation with relevant parties.
• Maintain version control of critical datasets and ensure backup procedures are strictly followed.

Qualifications and Requirements

• Minimum of one year of experience in data entry or a related administrative role.
• Proven organizational abilities and multitasking capacity.
• Exposure to basic project coordination activities.
• Comfort in handling numbers and meticulous attention to numerical accuracy.
• Ability to quickly learn and adapt to new software platforms.
• Excellent written communication skills, essential for remote coordination.
• A proactive approach to problem-solving.
• Reliability in meeting deadlines without the need for constant reminders.
• Demonstrated interest in process improvement and efficiency gains.
• Potential leadership qualities and initiative are appreciated.

Required Skills

• Data Entry
• Information Management
• Data Quality Assurance
• Training and Development Support
• Documentation and Procedure Writing
• Automation Identification
• Effective Communication (Written and Verbal)
• Problem Solving
• Organizational Skills
• Multitasking
• Project Coordination
• Attention to Numerical Accuracy
• Software Learning Ability
• Deadline Management
• Process Improvement

Work Environment and Operations

This is a full-time, remote position, based in Medina, Medina, Saudi Arabia. Candidates are expected to have a dedicated, distraction-free workspace, maintain consistent availability during agreed-upon working hours, and be responsive via email and messaging platforms. Participation in video conferences for team coordination is also required, along with self-discipline to maintain productivity without direct physical supervision.

RecruitLyticx Hires provides guidance on effective remote work practices and ergonomic recommendations for home office setups. This role offers a stepping stone towards careers in data management, quality assurance, or operations coordination, developing transferable skills in data governance, cross-functional collaboration, and digital workflow optimization.

We are looking for a Food Quality and Safety Specialist with field experience and a passion for improving operational practices in food factories and establishments. The candidate will be responsible for field visits, identifying challenges and risks related to food safety, root cause analysis, and providing practical solutions and recommendations that raise the level of compliance and quality for clients.

Key Responsibilities
Conduct field visits to food factories and establishments.
Assess the level of compliance with food safety requirements and related regulations.
Monitor and document observations and operational issues related to food quality and safety.
Analyze root causes of problems and provide effective corrective action plans and procedures.
Train and guide client teams on best practices.
Prepare technical reports and submit recommendations through the technical platform.
Collaborate with technical teams to develop solutions and improve customer experience.
Required Qualifications
Bachelor's degree in Food Science, Food Safety, Quality, or a related field.
At least 3 years of practical experience in food factories or establishments.
Good knowledge of food safety systems and standards such as HACCP, ISO 22000, and GMP.
Problem-solving and solution-finding skills.
Ability to prepare technical reports and communicate effectively with clients.
Willingness to travel and conduct field visits continuously.
Benefits

About the Role

YO IT Consulting is seeking a Neuroscience QA Lead for a remote, full-time contract position. This role is integral to overseeing the quality, consistency, and performance of AI training projects focused on neuroscience and cognitive science. The successful candidate will meticulously review AI-generated content and the work of trainers and QA specialists to ensure adherence to project guidelines and maintain high standards of scientific accuracy and conceptual precision.

This position offers an opportunity to contribute to a growing AI Data Services company that collaborates with leading AI firms and foundation-model labs. The role directly impacts the development of AI models by ensuring the accuracy, evidence-awareness, ethical appropriateness, and clarity of scientific training data. While there is no immediate project assignment, qualified candidates will be considered for relevant future opportunities and gain access to the company's expert network.

Key Responsibilities

• Conduct quality monitoring through spot-checking neuroscience/cognitive science items, identifying quality issues, and providing ongoing feedback to contributors.
• Escalate recurring or critical quality issues to the appropriate stakeholders.
• Perform scientific review of AI-generated neuroscience/cognitive science explanations, research summaries, experimental interpretations, brain-behavior claims, cognitive theory applications, and step-by-step reasoning for accuracy and clarity.
• Communicate updates to trainers and QAs via Discord regarding new item guidelines, project changes, workflow updates, quality expectations, and neuroscience/cognitive-science-specific review standards.
• Respond clearly and promptly to trainer/QA questions, particularly those concerning neural mechanisms, cognition, experimental design, statistical interpretation, ethical boundaries, clinical caution, and rubric interpretation.
• Manage trainer and QA activation by engaging inactive contributors, encouraging participation, tracking follow-ups, and flagging availability issues.
• Create and maintain comprehensive neuroscience/cognitive science project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
• Schedule and conduct onboarding and training sessions for trainers and QAs, detailing project expectations, workflows, rubrics, quality standards, and neuroscience/cognitive-science-specific review requirements.
• Ensure consistent application of neuroscience/cognitive science review guidelines by all trainers and QAs, and communicate updates as projects evolve.
• Conduct safety and ethics reviews, flagging pseudoscientific, overconfident, clinically misleading, ethically problematic, or unsupported claims about the brain, cognition, behavior, or mental health.
• Identify recurring quality gaps, propose workflow improvements, and contribute to building scalable QA processes for neuroscience/cognitive science AI training projects.

Qualifications and Requirements

• Bachelor's, Master's, PhD, MD/PhD, or equivalent professional background in Neuroscience, Cognitive Science, Psychology, Neurobiology, Cognitive Psychology, Computational Neuroscience, Neurology-adjacent research, Biology, Biomedical Sciences, or a closely related field.
• A strong command of the English language is essential for understanding project guidelines, communicating effectively with teams, and providing clear written feedback.
• A minimum of 3 years of experience in neuroscience/cognitive science research, teaching, laboratory work, academic review, science communication, experimental design, data analysis, or related scientific workflows.
• A robust understanding of neural systems, cognition, perception, attention, memory, learning, language, decision-making, neuroanatomy, neural signaling, research methods, and brain-behavior relationships.
• The ability to critically evaluate neuroscience/cognitive science content against detailed rubrics and identify issues such as neuromyths, overclaiming, unsupported causal conclusions, flawed study interpretation, incorrect terminology, pseudoscience, or misleading clinical implications.
• Experience with tools or methods such as EEG, fMRI, behavioral experiments, computational modeling, neuropsychological assessment, statistics, Python/R/MATLAB, cognitive tasks, or literature review is preferred.
• Previous experience leading or supporting remote teams of researchers, reviewers, educators, annotators, science writers, or QAs is strongly preferred.
• Comfort working in fast-moving remote environments utilizing tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
• Exceptional attention to detail and organizational skills, with the capacity to maintain style guides, FAQs, trackers, onboarding materials, calibration tasks, and documentation.
• Prior experience with AI training, data annotation, LLM evaluation, scientific QA, academic review, psychology/neuroscience content review, or rubric-based review is a strong plus.

Required Skills

• Neuroscience
• Cognitive Science
• Quality Assurance
• Structured Communication
• Attention to Detail
• Scientific Accuracy
• Research Literacy
• Experimental Method Understanding
• Brain-Behavior Reasoning
• Statistical Caution
• Ethical Awareness
• Clarity
• Formatting
• Instruction Following
• Project Rubrics Adherence
• Remote Team Management
• Discord
• Google Sheets
• Google Docs
• Project Management Systems
• AI Training Data
• Data Annotation
• LLM Evaluation
• Scientific QA
• Academic Review
• Psychology Content Review
• Rubric-Based Review

Work Environment and Contract Details

This is a remote, full-time contract position. The role requires working within fast-moving remote environments utilizing common collaboration and project management tools. While specific project assignments are not immediate, candidates will be considered for future opportunities within YO IT Consulting's AI Data Services division.

About the Role

Bechtel Corporation is seeking a Quality Assurance Engineer to join their team for the Ar Rjum Project. This full-time, office/project-based role is located in Taif, Saudi Arabia. The position reports to the Project Quality Manager and is instrumental in ensuring the effective implementation of the project's quality program across all phases of work.

Project Context

The Ar Rjum Project is a greenfield gold development situated in the Central Arabian Gold Region, approximately 200 km north-east of Taif. The project encompasses open pit mining, a processing plant, tailings management facilities, and associated infrastructure. The Quality Assurance Engineer will play a key role in upholding quality standards throughout this significant undertaking.

Key Responsibilities

• Assist the Quality Manager in the implementation and communication of the project quality program and plan requirements.
• Lead and support initiatives such as People-Based Quality (PBQ), Lessons Learned, Closed Loop Corrective Actions, Continuous Improvement, and Best Practices.
• Prepare quality audit checklists and coordinate, lead, or support internal and external audits and surveillances.
• Maintain liaison with client quality representatives and support the Quality Manager during client or regulatory audits.
• Support the development, maintenance, and execution of the Project Quality Audit & Surveillance Schedule.
• Monitor quality activities in engineering, procurement, and construction to ensure compliance with approved quality plans, procedures, and specifications.
• Review and determine applicable quality and regulatory requirements, report new or revised regulations, and support QA procedure development and revision.
• Coordinate and perform inspections and surveillances at site and vendor locations, maintain accurate inspection records, and issue Non-Conformance Reports (NCRs).
• Assist in root cause analysis and closed-loop corrective action processes.
• Participate in the prequalification of subcontractors and suppliers by evaluating their quality systems and reviewing submittals.
• Provide training and guidance to project personnel on quality requirements and procedures.
• Report weekly/monthly quality progress to the Project Quality Manager.

Qualifications and Experience

• Bachelor’s degree in Engineering, preferably Electrical Engineering.
• ISO 9001:2015 Certified Lead Auditor (IRCA approved) is required.
• Additional certifications in Quality (*, Six Sigma, Lean) are preferred.
• Minimum 10–12 years of relevant experience, including at least 8 years in a quality supervisory role.
• Experience in QA/QC activities across engineering, procurement, and construction phases.
• Previous experience with National Grid (NG) and Saudi Electricity Co (SEC) specifications and projects is beneficial.

Required Knowledge and Skills

• Strong understanding of quality assurance principles and ISO standards.
• Ability to interpret technical specifications, drawings, and quality plans.
• Proficiency in key performance quality matrices, root cause analysis, and corrective action systems.
• Capability to provide direction and on-the-job training.
• Proficiency in oral and written communication.
• Excellent communication, stakeholder management, and presentation skills.
• Proven skills in Microsoft Office and Power BI (High Level Performance).
• Ability to work collaboratively and lead quality activities effectively.
• Experience in developing training materials and conducting training, particularly in soft skills and quality audits/surveillances.