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Freelance Machine Learning Data Annotation Jobs in Vancouver, BC

Senior Machine Learning Developer Vancouver - Hybrid Job Summary Shape the future of AI in mining ... and data-driven innovation? Join Weir Motion Metrics and make a lasting impact on some of North ...

Senior Machine Learning Engineer

Burnaby, BC · On-site

CA$168K - CA$210K/yr

Partner with data scientists, product owners, and engineers across verticals to turn prototypes into reliable, customer-facing ML systems. * Optimize models and pipelines using MLOps best practices ...

Are you a technically strong and businessoriented Machine Learning / AI Engineer with a passion for ... Collaborate with data engineers to ensure reliable, scalable data pipelines that support model ...

The Data Science team is responsible for developing advanced AI and machine learning solutions that power critical products across Mastercard's network. This role will support the merchant/acquiring ...

Showing results 21-40

Freelance Machine Learning Data Annotation information

What is freelance machine learning data annotation?

Freelance machine learning data annotation involves labeling or tagging data—such as images, text, audio, or video—to help train machine learning models. As a freelancer, you work independently or through platforms, completing specific annotation tasks assigned by companies or researchers. This work is essential because high-quality labeled data is required for AI systems to learn and make accurate predictions. Annotators may categorize images, transcribe speech, or highlight relevant information in documents. The flexibility of freelancing allows you to choose projects and work remotely.

What are the key skills and qualifications needed to thrive as a freelance machine learning data annotation specialist?

To thrive as a Freelance Machine Learning Data Annotation specialist, you need attention to detail, basic knowledge of data labeling concepts, and familiarity with machine learning data types. Experience with annotation tools (such as Labelbox, RectLabel, or CVAT) and understanding of data privacy protocols are commonly required. Strong communication, time management, and the ability to follow complex guidelines are essential soft skills for delivering accurate results. These skills ensure high-quality, consistent data annotation, which is critical for effective machine learning model training and performance.

What are some common challenges faced by freelance machine learning data annotators, and how can they be managed?

Freelance machine learning data annotators often encounter challenges such as maintaining data accuracy, handling repetitive tasks, and understanding complex annotation guidelines. Staying organized and regularly reviewing project instructions can help ensure consistency and quality in annotations. Additionally, communicating proactively with project managers and utilizing annotation tools efficiently can help manage workload and clarify uncertainties. Building expertise in different data types (text, image, audio) also allows annotators to diversify their projects and reduce monotony.

What is the difference between Freelance Machine Learning Data Annotation vs Data Labeler?

AspectFreelance Machine Learning Data AnnotationData Labeler
CredentialsBasic understanding of annotation tools, sometimes with specialized domain knowledgeTypically no formal credentials required
Work EnvironmentRemote, flexible, project-basedOften remote or in-house, depending on employer
Industry UsageUsed in AI/ML development for training datasetsUsed in data preparation for various industries, including AI
Search/Comparison IntentFocuses on freelance opportunities, project scope, and toolsMore general, often employed by companies for data labeling tasks

Freelance Machine Learning Data Annotation involves independently completing annotation tasks for AI models, often with specialized tools and domain knowledge. Data Labelers typically perform similar tasks but may work as employees or contractors within a company. The main difference lies in the freelance nature and project-based work of data annotation roles.

Can I work for freelance machine learning data annotation with no experience?

Freelance machine learning data annotation jobs often do not require prior experience, as many tasks involve simple labeling or categorization that can be learned quickly. Basic computer skills, attention to detail, and familiarity with annotation tools are helpful, and training is usually provided. However, building a portfolio or gaining some familiarity with data annotation platforms can improve job prospects.

What are the most commonly searched types of Machine Learning Data Annotation jobs in Vancouver, BC?

The most popular types of Machine Learning Data Annotation jobs in Vancouver, BC are:

What are popular job titles related to Freelance Machine Learning Data Annotation jobs in Vancouver, BC?

For Freelance Machine Learning Data Annotation jobs in Vancouver, BC, the most frequently searched job titles are:

What job categories do people searching Freelance Machine Learning Data Annotation jobs in Vancouver, BC look for?

The top searched job categories for Freelance Machine Learning Data Annotation jobs in Vancouver, BC are:

Infographic showing various Freelance Machine Learning Data Annotation job openings in Vancouver, BC as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 16% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

Machine Learning Research Engineer

Royal Bank of Canada

Vancouver, BC • On-site

Full-time

Re-posted 11 days ago


Job description

Job Description

What's the opportunity?

At RBC Borealis, you'll be joining a team of leading researchers and software engineering specializing in machine learning. You will have access to rich and massive datasets, and to computational resources to support novel product development touching machine learning areas such as generative AI, natural language processing, and time series analysis.

We're looking for an enthusiastic Machine Learning Research Engineer who's excited by the opportunity of being at the forefront of applying machine learning technology to challenging problems. As a ML Research Engineer in the applied research team, you'll be part of a collaborative group who aims to deliver AI projects end to end - everything from data pre-processing and exploration, to prototyping novel algorithmic solutions, to software implementations of machine learning-based products. The goal is to understand the needs of our business partners and bring to life these unique and efficient solutions that can only be achieved through the use of machine learning.

Your responsibilities include:

  • Building machine learning-based software solutions;

  • Collaborating with business stakeholders to prototype machine-learning solutions rapidly;

  • Conducting comparisons to existing algorithms and baselines;

  • Reviewing, extending, and optimizing prototype solutions;

  • Collaborating with the engineering team to integrate algorithms into products;

  • Developing reusable internal tools to facilitate research prototyping;

  • Supporting projects with thorough documentation, design decisions, and capabilities.

You're our ideal candidate if you have:

  • A master's or PhD degree in computer science, mathematics, physics, economics or equivalent;

  • 2+ years of applied machine learning experience in a high-responsibility, minimal-supervision environment;

  • Experience with writing modular, robust, scalable software in Python 3.x;

  • Expertise in a few of the following areas: deep learning, natural language processing, information retrieval;

  • Experience with deep learning packages such as PyTorch, JAX, or Tensorflow;

  • Knowledge of professional software engineering best practices for the full software development life cycle, including testing methods, coding standards, code reviews, and source control management;

  • Strong communication skills and a collaborative attitude.

What's in it for you?

  • Become part of a team that thinks progressively and works collaboratively. We care about seeing each other reach full potential;

  • A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock options where applicable;

  • Leaders who support your development through coaching and managing opportunities;

  • Ability to make a difference and lasting impact from a local-to-global scale.

About RBC Borealis

RBC Borealis, an RBC Institute for Research, is a curiosity-driven research centre dedicated to achieving state-of-the-art in machine learning. Established in 2016, and with labs in Toronto, Montreal, Waterloo, and Vancouver, we support academic collaborations and partner with world-class research centres in artificial intelligence. With a focus on ethical AI that will help communities thrive, our machine learning scientists perform fundamental and applied research in areas such as reinforcement learning, natural language processing, deep learning, and unsupervised learning to solve ground-breaking problems in diverse fields.

Inclusion and Equal Opportunity Employment

RBC is an equal opportunity employer committed to diversity and inclusion. We are pleased to consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veterans status, Aboriginal/Native American status or any other legally-protected factors. Disability-related accommodations during the application process are available upon request.

#Ll-POST

Job Skills

Analytical Thinking, Decision Making, Detail-Oriented, Long Term Planning, Machine Learning (ML), Product Development Design, Programming Languages, Quantitative Research, Research and Development Operations, Research Documents

Additional Job Details

Address:

401 GEORGIA ST W:VANCOUVER

City:

Vancouver

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

TECHNOLOGY AND OPERATIONS

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2026-06-23

Application Deadline:

2026-08-31

Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Our Employment Opportunities

At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.

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Expand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at jobs.rbc.com.

RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.

Employment Type: FULL_TIME