ZipRecruiter

Log In

1

Virtual Data Labelling Jobs in Valley Stream, NY

MUFG

Network Infrastructure, Director

Jersey City, NJ · Hybrid

... networks across data centers, WAN, cloud environments, and voice environments. The position ... Cisco routers, switches, firewalls, F5 load-balancers, virtual private network (VPN) concentrators ...

MUFG

Network Infrastructure, Director

New York, NY · Hybrid

... networks across data centers, WAN, cloud environments, and voice environments. The position ... Cisco routers, switches, firewalls, F5 load-balancers, virtual private network (VPN) concentrators ...

CP Unlimited

Cloud & Security Engineer

Manhattan, NY · Remote

$61 - $81.75/hr

Support Microsoft Purview capabilities including data loss prevention, sensitivity labels ... Support Azure cloud infrastructure including subscriptions, resource groups, virtual networks ...

K Health

Senior Software Engineer - Full Stack

New York, NY · On-site

$160K - $200K/yr

We don't just build apps; we build, and operate modern, AI-powered, 24/7 virtual clinics for the ... Experience building reusable frameworks, white-label solutions, or multi-tenant architectures where ...

next page

Showing results 1-20

All JobsData Labelling JobsVirtual Data Labelling JobsVirtual Data Labelling Jobs in Valley Stream, NY

Virtual Data Labelling information

See Valley Stream, NY salary details

$48.1K

$172.6K

$254.7K

How much do virtual data labelling jobs pay per year?

As of Jul 31, 2026, the average yearly pay for virtual data labelling in Valley Stream, NY is $172,633.00, according to ZipRecruiter salary data. Most workers in this role earn between $139,700.00 and $177,800.00 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 Valley Stream, NY are hiring for Virtual Data Labelling jobs? Cities near Valley Stream, NY with the most Virtual Data Labelling job openings:
Virtual Data Labelling jobs near you

Senior Python Engineer - AI Coding Agent Evaluation (Freelance)

Mindrift

New York, NY • On-site, Remote

$200/hr

Part-time

Posted 15 days ago

Job description

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:
  • 8+ years in software development
  • Core stack: Python (FastAPI), JavaScript/TypeScript (React), Docker, Postgres, Kafka, Redis
  • Experience writing tests (functional, integration)
  • English proficiency - B2+

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 paidEffort estimate
Tasks for this project are estimated to take 30 hours to complete, depending on complexity. This is an estimate and not a schedule requirement; you choose when and how to work. Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.
Compensation:
Up to $200/hr equivalent, depending on level and pace. Tasks are estimated at ~30 hours each; you set your own schedule.

Apply