ZipRecruiter

Log In

1

Virtual Data Labelling Jobs in Snohomish, WA (NOW HIRING)

Meta

Taxonomist, Content Design

Seattle, WA · On-site +1

$120K/yr

... and data scientists to ensure that how Meta organizes, labels, and surfaces information is ... Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual ...

UnitedHealth Group

Lab Clerk

Everett, WA

Join us at our Washington Phlebotomists Virtual Hiring Event to learn more about this position ... Review data in the laboratory information system, label specimens, centrifuge, aliquot, and load ...

UnitedHealth Group

Lab Clerk

Everett, WA

Join us at our Washington Phlebotomists Virtual Hiring Event to learn more about this position ... Review data in the laboratory information system, label specimens, centrifuge, aliquot, and load ...

UnitedHealth Group

Lab Clerk

Everett, WA · On-site

Join us at our Washington Phlebotomists Virtual Hiring Event to learn more about this position ... Review data in the laboratory information system, label specimens, centrifuge, aliquot, and load ...

McKesson Corporation

Pharmacy Technician

Everett, WA · On-site

$22.06 - $36.76/hr

... labels for bottles. Assists Pharmacist to prepare and dispense medication. Receives and stores ... Counts stock and enters data in compute to maintain inventory records. Processes records of ...

Meta

Taxonomist, Content Design

Seattle, WA · On-site

$120K - $171K/yr

... and data scientists to ensure that how Meta organizes, labels, and surfaces information is ... Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual ...

Amazon

Mechanical Design Engineer, AFT Quality

Bellevue, WA · On-site

$85K - $116K/yr

... data-collection systems at scale. These systems will be installed in a large variety of ... Our team collaborates with machine learning scientists, fulfillment associates, labeling teams ...

All JobsData Labelling JobsVirtual Data Labelling JobsVirtual Data Labelling Jobs in Snohomish, WA

Virtual Data Labelling information

See Snohomish, WA salary details

$50.4K

$180.8K

$266.8K

How much do virtual data labelling jobs pay per year?

As of Aug 4, 2026, the average yearly pay for virtual data labelling in Snohomish, WA is $180,841.00, according to ZipRecruiter salary data. Most workers in this role earn between $146,300.00 and $186,300.00 per year, depending on experience, location, and employer.

What is the difference between Virtual Data Labelling vs Data Annotation Specialist?

AspectVirtual Data LabellingData Annotation Specialist
CredentialsBasic computer skills, training in labelling toolsSimilar, often requires training in annotation software
Work EnvironmentRemote, online platformsRemote or on-site, depending on employer
Industry UsageAI, machine learning, autonomous vehiclesAI, computer vision, NLP projects
Search IntentLabeling data for AI modelsAnnotating data for machine learning

Both roles involve preparing data for AI systems, but Virtual Data Labelling focuses on assigning labels to datasets using online tools, while Data Annotation Specialists may perform more detailed annotations, often requiring specific domain knowledge. Both are essential in AI development and share similar work environments and skill requirements.

What is virtual data labelling?

Virtual data labelling is the process of annotating or tagging data, such as images, videos, or text, through online platforms to make it understandable for machine learning algorithms. Data labelers work remotely to identify and categorize objects, features, or information within datasets, which helps train artificial intelligence systems. This job is essential in industries like autonomous vehicles, healthcare, and e-commerce, where large volumes of labelled data are needed to improve AI accuracy.

How does a virtual data labeller typically collaborate with data scientists and machine learning engineers?

Virtual data labellers play a crucial role in supporting data scientists and machine learning engineers by accurately tagging data that will be used to train and validate models. Collaboration often occurs through project management tools or direct communication platforms, where labellers receive guidelines and feedback to ensure consistency and quality. Regular check-ins or quality audits are common, and labellers may join virtual meetings to clarify requirements or discuss ambiguous cases. This teamwork helps ensure that the labelled data meets project standards and contributes to the success of AI initiatives.

What are the key skills and qualifications needed to thrive as a virtual data labeller, and why are they important?

To thrive as a Virtual Data Labeller, you need strong attention to detail, accuracy, and basic data processing skills, typically supported by a high school diploma or relevant experience. Familiarity with data annotation tools, content management systems, and sometimes basic programming or spreadsheet software is important. Strong time management, focus, and effective communication skills help you meet deadlines and collaborate with remote teams. These abilities are crucial to ensure high-quality, consistent data labelling that directly impacts the performance of machine learning models.
What cities near Snohomish, WA are hiring for Virtual Data Labelling jobs? Cities near Snohomish, WA with the most Virtual Data Labelling job openings:
Virtual Data Labelling jobs near you

Senior Software Engineer (Python) - Agent Evaluation - Freelance/Remote 100+ openings

Braintrust

Seattle, WA • On-site

$138K - $186K/yr

Other

This job post has expired today. Applications are no longer accepted.

Job description

***This opportunity is intended for experienced Senior Python Engineers only****


Open to candidates in the North America, South America, Asia and Europe.
Please submit your CV in English and indicate your level of English proficiency.

Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.


What this opportunity involves 

We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.

You'll create challenging tasks and evaluation criteria within realistic simulated environments:

  • Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history
  • Design tasks from intermediate states of these environments - craft the prompt, define what "solved" means, and ensure the task is solvable by an AI agent
  • Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient
  • Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust

What this is NOT

  • Not data labeling
  • Not prompt engineering
  • Not writing code from scratch - the agent writes most of the code; you guide and evaluate

What we look for - You must meet all the requirements in order to be considered for this project:

  • 5+ years of professional experience with Python.
  • Strong experience with FastAPI, pytest, and async/await.
  • Hands-on experience with Docker, PostgreSQL, and CI/CD pipelines.
  • Proven experience writing and maintaining automated tests (not just executing them).
  • Full-stack experience with React and TypeScript is a plus.
  • English proficiency at B2 level or higher.
  • Availability to work 30+ hours per week.


Why this is hard 

Frontier models are already good at coding. Creating a task that genuinely challenges the best models is non-trivial. You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution. Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.


How it works

Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid


Hiring & Onboarding Process

The process is designed to move quickly and typically includes the following steps:

  1. App review and invitation to a virtual project introduction session (approximately 30 minutes)
  2. Platform registration and identity verification
  3. Technical assessment (approximately 35 minutes)
  4. Background check (completed at no cost to candidates)
  5. Onboarding and project-specific training tasks
  6. Begin production work!
Additional Requirements
  • Willingness to complete identity verification as part of the onboarding process.
  • Ability to complete a technical assessment.
  • Willingness to join and participate in Discord, which will be used for project communication and updates.
  • Successful completion of a background check is required prior to onboarding.
  • Reliable internet connection and ability to communicate effectively in a remote environment.

Apply