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At Home Image Annotation Jobs in New York (NOW HIRING)

Teleskope

Jr. AI Engineer - Data Annotation

New York, NY · On-site

$75K - $90K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Teleskope continuously scans, catalogs, and classifies data in-motion and at-rest while automating ... Flexible vacation and work-from-home days. * Competitive salary and meaningful equity. * Health ...

Stackruit Ltd.

Senior AI Dataset Engineer

Manhattan, NY · On-site

$120 - $150/hr

Auto-Annotation Development: Create workflows for auto‑annotation of image and video data (e.g ... Join us at Reality Defender and be part of a team that's at the forefront of security technology ...

Visia

ML Engineer

New York, NY · On-site +1

$170K - $185K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

You'll primarily build the tooling and automation that powers our annotation, model training, and data pipelines, ensuring that every image we process makes Solstice better at understanding the ...

Job Haines at Home

CHHA

Montclair, NJ · On-site

$16.75 - $20/hr

A valid New Jersey Board of Nursing, home Health Aide certification is required. * Ability to read ... Complete at least twelve (12) hours of in-service training annually. OTHER DUTIES and ...

Job Haines at Home

CHHA

Montclair, NJ · On-site

$16.75 - $20/hr

A valid New Jersey Board of Nursing, home Health Aide certification is required. * Ability to read ... Complete at least twelve (12) hours of in-service training annually. OTHER DUTIES and ...

Job Haines at Home

CHHA

Montclair, NJ · On-site

$16.75 - $20/hr

A valid New Jersey Board of Nursing, home Health Aide certification is required. * Ability to read ... Complete at least twelve (12) hours of in-service training annually. OTHER DUTIES and ...

7-ELEVEN

Facilities Image Technician

Bay Shore, NY · On-site

$18 - $32/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Whether it's ensuring our famous Slurpee machines are always at the perfect chill or tackling in ... Join our team to fuel your career and make a meaningful impact in the places you call home. Apply ...

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All JobsAt Home Image Annotation JobsAt Home Image Annotation Jobs in New York

At Home Image Annotation information

What is the difference between At Home Image Annotation vs Data Labeler?

AspectAt Home Image AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, home-basedRemote, home-based or office
Industry UsageAI training, autonomous vehicles, medical imagingMachine learning, AI datasets, various industries
Job FocusAnnotating images for AI modelsLabeling data for machine learning

Both At Home Image Annotation and Data Labeler roles involve preparing data for AI systems, often working remotely with similar skills. However, At Home Image Annotation specifically emphasizes annotating images, while Data Labeler may include a broader range of data types. The roles are often interchangeable depending on the project, but understanding the specific focus can help in job selection.

What are common challenges faced by at home image annotation professionals, and how can they be managed?

At-home image annotation professionals often face challenges such as maintaining focus during repetitive tasks, meeting tight deadlines, and ensuring high accuracy in their work. To manage these, it's helpful to set up a dedicated workspace, use productivity techniques like the Pomodoro method, and regularly review guidelines to minimize errors. Collaborating through online team channels and seeking feedback can also help maintain quality and stay connected with the team, even while working remotely.

What is at home image annotation?

At home image annotation is a remote job where individuals label or tag objects, features, or areas within digital images to help train artificial intelligence (AI) systems. This process involves using specialized software to draw boxes, outlines, or points on images and assign labels to them based on specific instructions. The annotated images are then used by companies to improve machine learning models for tasks such as image recognition, autonomous vehicles, and medical diagnostics. Working from home, annotators usually need a computer, reliable internet, and attention to detail. The job is often flexible and can be done part-time or full-time.

What skills and qualifications are needed for at home image annotation?

To thrive as an At Home Image Annotation Specialist, you need attention to detail, strong visual perception, and a basic understanding of data labeling concepts, usually supported by a high school diploma or equivalent. Familiarity with annotation platforms like Labelbox, Supervisely, or VIA, and sometimes experience with basic image editing tools, is often required. Strong self-motivation, communication skills, and the ability to follow complex instructions help individuals excel in remote, independent work environments. These skills ensure high-quality, accurate datasets that are crucial for training reliable computer vision models.
What are the most commonly searched types of Image Annotation jobs in New York? The most popular types of Image Annotation jobs in New York are:
What are popular job titles related to At Home Image Annotation jobs in New York? For At Home Image Annotation jobs in New York, the most frequently searched job titles are:
What job categories do people searching At Home Image Annotation jobs in New York look for? The top searched job categories for At Home Image Annotation jobs in New York are:
What cities in New York are hiring for At Home Image Annotation jobs? Cities in New York with the most At Home Image Annotation job openings:
At Home Image Annotation jobs near you
Infographic showing various At Home Image Annotation job openings in New York as of August 2026, with employment types broken down into 70% Full Time, 10% Part Time, and 20% Contract. Highlights an 90% In-person, and 10% Remote job distribution.

Jr. AI Engineer - Data Annotation

Teleskope

New York, NY • On-site

$75K - $90K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 23 days ago

Job description

About Teleskope
Teleskope is redefining data security for the AI era with the only dedicated platform that combines precise visibility with automated remediation. Teleskope continuously scans, catalogs, and classifies data in-motion and at-rest while automating policy-based actions, helping organizations proactively manage data sprawl while securely enabling AI adoption.
Fresh off our $25 million Series A round, Teleskope is entering a high-growth phase backed by top-tier investors and exceptional product-market fit.
About the Role
We're looking for a hungry, hands-on AI Engineer to join our data science team. You'll do the work directly, labeling and reviewing classification data and running QC, but you won't just execute. You'll bring an engineer's mindset to it: when a task is repetitive, you script it; when quality is hard to measure, you build a way to measure it. You'll use Python, SQL, and agentic development tools to make annotation and QC faster, more consistent, and more scalable.
This is a rapidly evolving role, and we expect you to context switch comfortably as priorities shift. You'll work shoulder-to-shoulder with data scientists and ML engineers, people who think about data the way you do, and the labels and quality signals you produce feed directly into the models that protect real customers' most sensitive data. The work is high-impact and the data is messy; a big part of the job is learning, through the work itself, what it takes to make it usable.
This is a hybrid role requiring 3+ days in-office in New York City.
Who Should Apply
We're looking for someone with programming ability, dependability, and the drive to learn on the job. Recent grads are welcome, and CS and STEM backgrounds are a great fit. What matters most is that you can think critically, you're excited to work through messy data, you can context switch as priorities change, and you want to grow fast in a fast-moving environment.
What You'll Do
  • Do hands-on data annotation and quality control (labeling, reviewing, and correcting classification outputs) as a core member of the data science pipeline.
  • Take ownership of improving and scaling the process: find the bottlenecks, repetitive steps, and sources of error, and fix them with Python, SQL, and agentic workflows.
  • Build and run quality control checks that catch labeling errors, measure inter-annotator agreement, and surface systematic issues before they reach production.
  • Work closely with data scientists and ML engineers to close the loop between real-world performance and model improvement.
  • Context switch across labeling, quality analysis, scripting, and process work as priorities evolve.
  • Document QC processes and annotation guidelines to support team scaling and onboarding.
About You
  • Solid programming ability, with hands-on Python experience and a willingness to dig into scripts, SQL, and data wrangling.
  • Comfortable using agentic development tools, or eager to ramp up on them fast.
  • A quality-first mindset. You notice when something is off in the data and won't let it slide.
  • Dependable and adaptable. Teammates can count on you, and you stay effective as priorities shift.
  • Energized by messy, real-world data and by working alongside other data-minded people.
  • Hungry, self-directed, and ready to grow with Teleskope as we scale.
Nice to Have
  • Familiarity with feedback loops in ML systems and how label quality connects to model performance.
  • Experience with annotation platforms (Label Studio, Prodigy, Scale, or custom-built systems).
  • Familiarity with active learning or online learning approaches.
  • Experience with SQL and building lightweight dashboards to track quality metrics.
  • Background in NLP or text classification workflows.
What You'll Get
  • A seat alongside data scientists and ML engineers, data-minded people to learn from every day.
  • Work that visibly matters. Your labels feed the models that protect real customers' most sensitive data.
  • Ownership of the annotation and quality processes that determine classification accuracy across the platform.
  • Room to grow fast, with real ownership from day one as Teleskope scales.
  • A beautiful, well-stocked office in NYC's Financial District.
  • Flexible vacation and work-from-home days.
  • Competitive salary and meaningful equity.
  • Health, vision, dental, 401k, and more benefits, heavily subsidized by Teleskope.
What We Value
At Teleskope, we value builders who care about the details. This role is for someone who sees data quality not as a support function but as a force multiplier, and who takes pride in making the people around them more effective. We look for dependable teammates who ship iteratively, take ownership, and understand that great ML starts with great data.

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