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No Experience Machine Learning Data Annotation Jobs in New York

Welocalize, Inc.

Data Quality Analyst

New York, NY · On-site

The ideal candidate will have a foundational understanding of machine learning, data annotation ... Experience: * Ability to work in a fast-paced, collaborative environment. * Excellent communication ...

Welocalize, Inc.

Data Quality Analyst

New York, NY · On-site

The ideal candidate will have a foundational understanding of machine learning, data annotation ... Experience: * Ability to work in a fast-paced, collaborative environment. * Excellent communication ...

Welocalize, Inc.

Data Labeling Associate

New York, NY · On-site

$17.50 - $22.75/hr

The ideal candidate will have a foundational understanding of machine learning, data annotation ... Experience: * Ability to work in a fast-paced, collaborative environment. * Excellent communication ...

TSMG

AI/ML Data Contributor

New York, NY · Remote

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

New York, NY

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

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No Experience Machine Learning Data Annotation information

What is a no experience machine learning data annotation job?

'No Experience Machine Learning Data Annotation' jobs are entry-level positions where individuals help label and categorize data used to train machine learning models. These roles do not require prior experience in data science or programming, making them accessible to beginners. Typical tasks may include tagging images, transcribing audio, or identifying objects in videos. These jobs are essential for improving the accuracy of AI systems and are often done remotely or on a flexible schedule.

What should I expect when collaborating with machine learning engineers as a data annotator with no prior experience?

As a data annotator working alongside machine learning engineers, you will play a vital role in preparing high-quality labeled data for model training. Engineers often provide clear guidelines and feedback on how to label or categorize data accurately, and they may hold regular check-ins to address questions and ensure consistency. While you may not need technical expertise, strong communication and attention to detail are essential, as your work directly impacts the performance of machine learning models. Over time, you’ll become familiar with annotation tools and may have the opportunity to take on more advanced tasks or quality assurance responsibilities.

What are the key skills and qualifications needed to thrive as a no experience machine learning data annotation specialist, and why are they important?

To succeed in a No Experience Machine Learning Data Annotation role, you need strong attention to detail, basic computer literacy, and the ability to follow precise instructions, often requiring at least a high school diploma. Familiarity with data labeling tools (like Labelbox or Supervisely) and experience with spreadsheet software are typically helpful, though many positions offer on-the-job training. Reliability, patience, and effective communication are valuable soft skills for maintaining quality and meeting deadlines. These skills ensure accurate, consistent data labeling, which is critical for training reliable machine learning models.

What is the difference between No Experience Machine Learning Data Annotation vs Data Labeling Specialist?

AspectNo Experience Machine Learning Data AnnotationData Labeling Specialist
Required CredentialsNo formal experience needed, training providedTypically similar, may require basic technical skills
Work EnvironmentRemote or office-based, repetitive tasksRemote or onsite, focused on data preparation
Industry UsageCommon in AI/ML companies, tech startupsUsed across tech, automotive, healthcare sectors
Search & Comparison IntentOften searched by beginners or entry-level job seekersCompared for skill requirements and job scope

Both roles involve labeling data for machine learning models, with minimal experience required. Data Labeling Specialists may have slightly more specialized tasks, but both are entry-level positions vital for AI development.

What are the most commonly searched types of Machine Learning Data Annotation jobs in New York?

The most popular types of Machine Learning Data Annotation jobs in New York are:

What are popular job titles related to No Experience Machine Learning Data Annotation jobs in New York?

For No Experience Machine Learning Data Annotation jobs in New York, the most frequently searched job titles are:

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The top searched job categories for No Experience Machine Learning Data Annotation jobs in New York are:

What cities in New York are hiring for No Experience Machine Learning Data Annotation jobs?

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No Experience Machine Learning Data Annotation jobs near you
Infographic showing various No Experience Machine Learning Data Annotation job openings in New York as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Data Quality Analyst

Welocalize, Inc.

New York, NY • On-site

Full-time

Posted 4 days ago

Welocalize rating

6.5

Company rating: 6.5 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

339th of 500 rated business services

Job description

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Job Responsibilities:

The ideal candidate will have a foundational understanding of machine learning, data annotation, quality assurance, and natural language processing. They will play a pivotal role in updating our machine learning models and ensuring their efficacy.

MAIN TASKS & RESPONSIBILITIES

Machine Learning Model Updates:

  • Update training and test model databases with new or amended synthetic textual and image data.
  • Modify and refine machine learning data creation, annotation, and rating guidelines.

Model Training and Evaluation:

  • Initiate model training processes using internal tools and command-line interfaces.
  • Evaluate the performance of trained models to gauge their efficacy and readiness for deployment.

Data Management and Annotation:

  • Design and develop test and training datasets as per the criteria provided by the project manager and other full-time employees.
  • Handle data efficiently, ensuring its integrity throughout the workflow.
  • Engage in data relevance tasks, ensuring data sets are aligned with project goals.
  • Annotate data accurately, ensuring it adheres to set guidelines.

Quality Assurance and Analysis:

  • Conduct manual quality analysis of model results.
  • Recognize error patterns and report anomalies for further investigation.
  • Deliver detailed reports on findings, including aspects such as utterance quality, LLM evaluation, ASR bug tracking, and customer pain points to be reviewed by the User Experience Research team.
  • Implement basic quality control measures and ensure the reliability of processed data.
  • Utilize intermediate data analysis techniques to extract insights and inform decision-making.
  • Arbitrate discrepancies effectively, ensuring consistent data quality.

Linguistic and NLP Tasks:

  • Apply basic knowledge of natural language processing and linguistics to data processing tasks.
  • Ensure linguistic accuracy in all processed and annotated data.

REQUIREMENTS

Preferred Qualifications:

  • Bachelor's degree in Computer Science, Data Science, Linguistics or Computational Linguistics or a related field.

Experience:

  • Ability to work in a fast-paced, collaborative environment.
  • Excellent communication skills

Skills & Knowledge:

  • Familiarity with command-line tools and interfaces.
  • Strong analytical skills with the ability to identify patterns and anomalies.

Additional Information:

This role primarily focuses on English US data sets; however, familiarity with translation or multi-lingual data sets can be a plus for future projects.

Additional Job Details:

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