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Data Annotation For Ai Jobs in Alberta (NOW HIRING)

Royal Bank of Canada

Principal AI Engineer

Calgary, AB · On-site

We are looking for a Principle AI Engineer to drive the development of Data engineering solutions on RBC's Enterprise Data and AI Hybrid Multi-cloud Platforms, that meet the strategic data objectives ...

Accenture

AI LLM Technology Architecture

Calgary, AB · On-site

Architect the end-to-end data pipeline for AI systems, including data ingestion, preprocessing, and synchronization for fine-tuning and RAG. Design and implement the context layer-spanning knowledge ...

Blend360

AI and Data Engineer

Edmonton, AB · On-site

... data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles ... For more information, visit www.blend360.com We are building a team of engineers in Edmonton, AB ...

PwC

Manager Cyber Cloud Security and AI

Calgary, AB · Hybrid

CA$116K - CA$166K/yr

Establishpolicies and standards for AI security and data operations. Ensure compliance with applicable regulations, standards (e.g., GDPR, CCPA), and best practices in cyber resilience. * Team ...

Wawanesa Insurance

Senior Architect - Data & AI

Calgary, AB · Hybrid

CA$115K - CA$160K/yr

The salary offered for this role is determined with consideration to various factors, including but ... Job Overview Under moderate supervision, the Senior Architect - Data & AI, will contribute to ...

KPMG

Manager, ML/AI Engineer, Data & AI

Calgary, AB

Our team is looking for a handson engineer with deep experience in AI/ML engineering and AI/ML ... Collaborate with data engineers to ensure reliable, scalable data pipelines that support model ...

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Data Annotation For Ai information

What is data annotation for AI?

Data annotation for AI is the process of labeling or tagging data—such as text, images, audio, or video—to make it understandable for machine learning models. Annotators add relevant information to raw data, helping AI systems learn to recognize patterns and make accurate predictions. This step is crucial for training, validating, and testing AI algorithms, especially in tasks like computer vision and natural language processing. High-quality data annotation directly impacts the effectiveness and reliability of AI applications.

What are some common challenges faced by data annotators working on AI projects, and how can they be addressed?

Data annotators for AI often encounter challenges such as maintaining consistency across large datasets, understanding ambiguous labeling instructions, and managing repetitive tasks. To address these issues, it's important to actively seek clarification on guidelines, participate in team discussions to align on labeling standards, and use annotation tools that flag inconsistencies. Regular feedback sessions with project leads also help improve accuracy and efficiency, fostering a collaborative and supportive work environment.

What are the key skills and qualifications needed to thrive as a data annotation specialist for AI, and why are they important?

To thrive as a Data Annotation Specialist for AI, you need a keen eye for detail, a solid understanding of data labeling concepts, and often a background in the relevant domain (such as language, images, or audio). Proficiency with annotation platforms, data management systems, and basic familiarity with tools like Excel or Python can be highly valuable. Strong communication, consistency, and time management skills help ensure accuracy and meet project deadlines. These abilities are crucial because high-quality, well-annotated data is foundational for training reliable and effective AI models.

What is the difference between Data Annotation For Ai vs Data Labeler?

AspectData Annotation For AiData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, tech companies, AI projectsRemote or on-site, data processing companies
Industry UsageArtificial Intelligence, Machine LearningData management, content moderation
Job FocusPreparing data for AI algorithms through annotationLabeling data for various purposes, including AI

Data Annotation For Ai involves preparing datasets specifically for training AI models, focusing on detailed annotations. Data Labeler is a broader role that includes labeling data for multiple purposes, including AI but also other data management tasks. While both roles require similar skills, Data Annotation For Ai is more specialized towards AI development projects.

What are popular job titles related to Data Annotation For Ai jobs in Alberta?

For Data Annotation For Ai jobs in Alberta, the most frequently searched job titles are:

What job categories do people searching Data Annotation For Ai jobs in Alberta look for?

The top searched job categories for Data Annotation For Ai jobs in Alberta are:

Data Annotation For Ai jobs near you
Infographic showing various Data Annotation For Ai job openings in Alberta as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 14% Part Time, and 2% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution.

First-Person AI Video Trainer

Edmonton, AB • On-site

Mindrift - Data annotation
See more jobs at Mindrift - Data annotationexternal

Part-time

Re-posted 21 days ago

Job description

This is a project-based opportunity on an AI training platform - not a job. No fixed hours, no commitment beyond what fits your schedule. You record, you get paid.

About the Role

We're looking for people to record point-of-view videos of everyday household activities. You mount your smartphone on your head, go about your routine, and the camera captures exactly what you see. These videos help train AI systems and robots to understand how people interact with objects in real-world environments.
Do you wash dishes every day? Vacuum the rug? Walk the dog? Fold laundry? What if you could get paid just for recording it?

Responsibilities

  • Record everyday household activities from a first-person perspective - cooking, cleaning, tidying up, folding laundry, gardening, walking the dog, and more
  • Record in your own home, yard, garage, or workspace
  • Follow short recording guidelines per session
  • Upload videos through the project app

Requirements

  • Equipment: Own or use a smartphone or alternative camera device capable of 30 FPS or greater and 1080p resolution or greater. iPhone 12 or newer, Google Pixel 6+, or Samsung Galaxy S21+ (must have a wide-angle / 0.5x lens)
  • Capture method: Mount the device at forehead or eye-level for an egocentric perspective, maintaining a downward angle to maximize hand visibility.
  • Software: Utilize the designated "D&A" application for all data capture and upload.
  • Quality control: Ensure all video footage is clear, stable, well-lit, at least 15 seconds long, and accurately depicts useful, intentional tasks without unnecessary pauses or contrived movements.

Why is this freelance opportunity a great fit for you?

Earn while you do your household chores: up to $6 per hour equivalent depending on the project

This is project-based freelance work - pick up recording sessions when they fit your schedule

Influence the future of how AI and robots understand and interact with the real world

Apply