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Full Time Machine Learning Data Annotation Jobs (NOW HIRING)

Apple

Machine Learning Data Engineer

Cupertino, CA · On-site

$141K - $169K/yr

Description We are seeking a highly experienced and strategic Machine Learning Data Engineer to drive our machine learning data with a strong focus on quality. In this role, you will transform ...

Mercor

Senior Machine Learning Engineer

New York, NY · Remote

$70 - $100/hr

... experience in Machine Learning , Data Science , Software Engineering , Computer Science ... Prior experience with data annotation, labeling, evaluation, or human feedback collection.

Apple

Machine Learning Data Engineer

Cupertino, CA

$184K - $324K/yr

Description We are seeking a highly experienced and strategic Machine Learning Data Engineer to drive our machine learning data with a strong focus on quality. In this role, you will transform ...

FieldAI

2.53 3D Machine Learning Engineer

Irvine, CA · On-site

... data annotation strategies and ensure high model performance and generalization. Qualifications : Required : • Bachelor's or Master's degree in Computer Science, Machine Learning, Robotics, or a ...

Mercor

Data Science Expert - Fully Remote

New York, NY · Remote

$70 - $100/hr

... experience in Machine Learning , Data Science , Software Engineering , Computer Science ... Prior experience with data annotation, labeling, evaluation, or human feedback collection.

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Full Time Machine Learning Data Annotation information

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$37.5K

$122.7K

$196.5K

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

As of Jul 17, 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.

More about Full Time Machine Learning Data Annotation jobs
What cities are hiring for Full Time Machine Learning Data Annotation jobs? Cities with the most Full Time Machine Learning Data Annotation job openings:
What are the most commonly searched types of Machine Learning Data Annotation jobs? The most popular types of Machine Learning Data Annotation jobs are:
What states have the most Full Time Machine Learning Data Annotation jobs? States with the most job openings for Full Time Machine Learning Data Annotation jobs include:
What job categories do people searching Full Time Machine Learning Data Annotation jobs look for? The top searched job categories for Full Time Machine Learning Data Annotation jobs are:
Full Time Machine Learning Data Annotation jobs near you
Infographic showing various Full Time Machine Learning Data Annotation job openings in the United States as of July 2026, with employment types broken down into 2% Locum Tenens, 19% Full Time, 17% Part Time, 19% Contract, 42% Nights, and 1% Summer. Highlights an 34% Physical, and 66% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.
Machine Learning Data Engineer

Machine Learning Data Engineer

Apple

Cupertino, CA • On-site

$141K - $169K/yr

Full-time

Re-posted 4 days ago

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 670 frontline employees who took The Breakroom Quiz

5th of 30 rated technology retailers

Job description

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other's ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It's the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something - you'll add something.
Description
We are seeking a highly experienced and strategic Machine Learning Data Engineer to drive our machine learning data with a strong focus on quality. In this role, you will transform ambiguous data challenges into scalable processes, clear policies, and high-fidelity datasets that power diverse ML use cases, specifically focused on innovative consumer products and user-facing technologies.
You will act as the crucial link between technical tools and infrastructure, cross-functional engineering teams, and regulatory compliance (including privacy, legal, and consumer data protection). If your passion is making sense of complex data, designing data evaluation frameworks, and leading initiatives to maximize model ROI through rigorous data quality, we want you on our team.
Minimum Qualifications
BS in Computer Science, Data Engineering, Data Science, Mathematics, or a related field; or equivalent industry experience.
Experience in data analysis, data engineering, and machine learning data operations.
Experience designing data quality control processes, data curation workflows, or Human-in-the-Loop initiatives.
Experience managing or coordinating cross-functional projects spanning multiple technical teams or organizations, leading end-to-end data strategy for ML development lifecycle, including iterating rapidly to drive improvements.
Preferred Qualifications
10+ years of experience in data analysis or ML data operations, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.
Experience operating within global data privacy frameworks (e.g., GDPR, CCPA) and aligning consumer ML data handling with legal compliance and ethical guidelines.
Proven background in leading complex, cross-functional programs focused specifically on ML data quality at scale.
Experience with prompt engineering, machine learning tools, and fine-tuning Large Language Models (LLMs).
Demonstrated ability to consult with diverse engineering stakeholders to gather requirements, explain complex models, and iterate rapidly to drive improvements.
Excellent written and verbal communication skills, with a specialized ability to distill highly technical analyses to non-technical audiences effectively.
Exceptional problem-solving skills, adaptability, and agility to navigate high ambiguity, learn proprietary tools quickly, and thrive in a fast-paced environment.

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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