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Full Time Machine Learning Data Annotation Jobs (NOW HIRING)

Welocalize, Inc.

Data Quality Lead

San Francisco, CA · On-site

Stay updated with the latest in machine learning, data annotation, and natural language processing. * Address complex technical challenges faced by the team. * Provide guidance on advanced annotation ...

Welocalize, Inc.

Data Quality Lead

New York, NY · On-site

Stay updated with the latest in machine learning, data annotation, and natural language processing. * Address complex technical challenges faced by the team. * Provide guidance on advanced annotation ...

Welocalize, Inc.

Data Quality Lead

New York, NY · On-site

Stay updated with the latest in machine learning, data annotation, and natural language processing. * Address complex technical challenges faced by the team. * Provide guidance on advanced annotation ...

Welocalize, Inc.

Data Quality Lead

San Francisco, CA · On-site

Stay updated with the latest in machine learning, data annotation, and natural language processing. * Address complex technical challenges faced by the team. * Provide guidance on advanced annotation ...

Sunday Inc

Data Annotation Lead

Redwood City, CA · On-site

You'll work in coordination with Machine Learning, Software engineering, and Data to define the framework and tools on which to build a data annotation team around. Your role is vital to ensuring our ...

Welocalize, Inc.

Data Quality Analyst

New York, NY · On-site

The ideal candidate will have a foundational understanding of machine learning, data annotation ... other full-time employees. * Handle data efficiently, ensuring its integrity throughout the ...

Welocalize, Inc.

Data Labeling Associate

San Diego, CA

$17 - $22/hr

The ideal candidate will have a foundational understanding of machine learning, data annotation ... other full-time employees. * Handle data efficiently, ensuring its integrity throughout the ...

Welocalize, Inc.

Data Labeling Associate

San Diego, CA

$17 - $22/hr

The ideal candidate will have a foundational understanding of machine learning, data annotation ... other full-time employees. * Handle data efficiently, ensuring its integrity throughout the ...

Welocalize, Inc.

Data Quality Analyst

New York, NY

The ideal candidate will have a foundational understanding of machine learning, data annotation ... other full-time employees. * Handle data efficiently, ensuring its integrity throughout the ...

Welocalize, Inc.

Data Labeling Associate

New York, NY

$17.50 - $22.75/hr

The ideal candidate will have a foundational understanding of machine learning, data annotation ... other full-time employees. * Handle data efficiently, ensuring its integrity throughout the ...

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All JobsFull Time Machine Learning Data Annotation Jobs

Full Time Machine Learning Data Annotation information

See salary details

$37.5K

$122.7K

$196.5K

How much do full time machine learning data annotation jobs pay per year?

As of Jun 27, 2026, the average yearly pay for full time machine learning data annotation in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Full Time Machine Learning Data Annotation Specialist, and why are they important?

To thrive as a Full Time Machine Learning Data Annotation Specialist, you need strong attention to detail, basic data literacy, and familiarity with data labeling concepts, often supported by a high school diploma or equivalent. Proficiency in specialized annotation platforms, spreadsheet tools, and sometimes knowledge of Python or labeling frameworks is typically required. Reliability, patience, and effective communication are valuable soft skills for ensuring accuracy and collaborating with team members. These skills and qualities are crucial because they directly impact the quality of training data, which is essential for developing effective machine learning models.

What are Full Time Machine Learning Data Annotation jobs?

Full time machine learning data annotation jobs involve labeling, tagging, or categorizing data such as images, text, audio, or video to help train machine learning models. Data annotators play a crucial role in ensuring that AI systems learn from high-quality, accurately labeled datasets. These positions often require attention to detail, consistency, and sometimes familiarity with the subject matter or specialized tools. Full-time roles may be remote or onsite and can span industries like autonomous vehicles, healthcare, retail, and more.

What are some common challenges faced by machine learning data annotators, and how are these typically addressed within a team?

Machine learning data annotators often encounter challenges such as maintaining consistency in labeling, handling ambiguous data, and meeting tight deadlines for large datasets. Teams usually address these by establishing clear annotation guidelines, conducting regular training sessions, and implementing quality assurance processes like peer reviews and spot checks. Collaboration with data scientists and project managers is also common, ensuring that annotators can ask questions and clarify uncertainties, leading to higher-quality labeled data and a supportive work environment.

What is the difference between Full Time Machine Learning Data Annotation vs Data Labeling Specialist?

AspectFull Time Machine Learning Data AnnotationData Labeling Specialist
CredentialsHigh school diploma or equivalent; some roles prefer technical certificationsHigh school diploma or equivalent; training often provided on the job
Work EnvironmentOffice or remote; collaborative with data science teamsRemote or office; focused on labeling tasks
Industry UsageUsed across AI/ML companies, tech firms, and startupsCommon in AI/ML, data services, and outsourcing companies
Job FocusCreating labeled datasets for machine learning modelsAnnotating data such as images, videos, or text for AI training

Full Time Machine Learning Data Annotation involves creating high-quality labeled datasets for AI models, often requiring technical understanding. Data Labeling Specialists focus on annotating data accurately, typically with less emphasis on technical skills. Both roles are essential in AI development but differ mainly in scope and technical complexity.

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Full Time Machine Learning Data Annotation jobs near you
Software Engineer (ML Data & Annotation Pipelines)

Software Engineer (ML Data & Annotation Pipelines)

Diversified Services Network, Inc.

Mossville, IL • On-site

$83K - $100K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

Job description

Diversified Services Network, Inc. (DSN) is seeking a full-time Software Engineer – ML Data & Annotation Pipelines to join our team fully onsite in Mossville, IL! We offer full benefits, PTO, 401k, and more! If you are a Python-savvy engineer excited about building software tools that support autonomous vehicle machine learning workflows, improving user experiences, and leveraging modern AI-assisted development practices within an extremely reputable, stable Fortune 500 company — let’s talk!

Position Overview

We are seeking a Software Engineer to join our Annotation Team, fully on-site in Mossville, IL. This is a new addition to the team, offering hands-on exposure to the full annotation workflow for autonomous vehicles, from raw sensor data (rosbags) through 2D/3D labeling and machine learning dataset preparation.

You will primarily develop and enhance tooling used by teams creating training data for autonomous vehicle machine learning systems. Success in this role requires strong Python development skills combined with the ability to design intuitive user experiences, understand how end users interact with software, and proactively identify improvements that increase efficiency and usability. You will work across the stack, contributing to Python backend development, browser-based UI enhancements, annotation workflow improvements, and integrations between internal tools and machine learning data pipelines.

This role is ideal for a software engineer who enjoys building tools for other users and is passionate about creating intuitive, efficient experiences that improve how teams work.

Key Contributions & Responsibilities
  • Integrate the rosbag-to-COCO conversion pipeline into existing workflows.
  • Implement 2D → 3D projection mapping to integrate the auto-annotation pipeline.
  • Maintain and enhance the UI/UX for viewing 2D/3D annotations in CVAT (Computer Vision Annotation Tool).
  • Support model updates to the annotation pipeline, including the ability to swap out models as needed.
  • Build and maintain CI/CD infrastructure; work with data in AWS using push/pull workflows.
  • Add and update APIs to query from the CVAT REST API.
  • Collaborate via GitHub — creating pull requests, participating in code reviews, and writing design documentation.
  • Design and implement features that improve the efficiency, usability, and overall user experience of the annotation platform.
  • Partner with annotation users to understand workflows, gather feedback, and translate requirements into practical software solutions.
  • Anticipate user needs and identify opportunities to improve tooling before requirements are explicitly requested.
Team Structure & Work Environment
  • Your primary team consists of 8 individuals (1 Lead and 7 Developers); the project also involves collaborative development with 2 additional resources from another team. You will attend Annotation Team standups every other day, a weekly CVAT Team meeting, and project-related meetings as needed, with the remainder of your time dedicated to development.
  • Work involves a mix of independent feature development and paired code reviews, with regular collaboration through GitHub PRs, design doc discussions, and in-person or remote meetings.

Requirements

Education & Experience
  • 2–4 years of relevant experience required. Bachelor’s degree required.
Top 3 Skills
  • Python — core language for application development, workflow automation, platform enhancements, and integration work.
  • User-centered software development — ability to understand how users interact with tools and translate requirements into intuitive, efficient workflows.
  • Agentic coding best practices — experience leveraging AI-assisted development tools to accelerate software delivery, iteration, and problem solving.
Required Technical Skills
  • Python development experience.
  • Experience with annotation workflows, machine learning data pipelines, or adjacent software platforms supporting ML development.
  • Proficiency with Git/GitHub, including pull requests, code reviews, and branching workflows.
  • Experience developing user-facing applications, interfaces, dashboards, or internal productivity tools.
  • Ability to gather user requirements and translate them into functional software solutions.
Desired Technical Skills
  • JavaScript development experience.
  • Experience with CVAT or similar annotation tools.
  • Familiarity with ROS/rosbag data formats and knowledge of the COCO dataset format.
  • Experience with 3D object detection, image processing, computer vision workflows, or related technologies.
  • Experience building tools used by technical end users.
  • Familiarity with coordinate transforms (e.g., 2D → 3D projection).
  • Experience working with image visualization, image processing, or annotation-related applications.
  • AWS, Docker, API development, and CI/CD experience.
Required Soft Skills
  • Strong communication and product-thinking skills — able to understand user workflows, gather requirements, anticipate future needs, and translate feedback into practical software solutions.
  • Self-motivated and able to work independently with minimal supervision.
  • Collaborative mindset — comfortable working in small teams, giving and receiving code review feedback.
  • Problem-solving orientation — able to debug complex software and pipeline issues and propose creative solutions.
Desired Soft Skills
  • Comfort presenting technical concepts to non-technical stakeholders.
  • Proactive in identifying process improvements and suggesting enhancements.
  • Ability to see a solution beyond communicated requirements — focusing on how it will be used rather than simply whether it met requirements.

Benefits

  • 401(k)
  • Dental insurance
  • Vision Insurance
  • Disability insurance
  • Employee assistance program
  • Health insurance
  • Health savings account
  • Life insurance
  • Paid time off
  • Paid Holidays

Please follow the link to our website for a list of job openings in Engineering, IT, Project Management, and more! https://www.dsnworldwide.com

Compensation: $98,000 - $103,000 per year