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Full Time Machine Learning Data Annotation Jobs in Sunnyvale, CA

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 ...

Encord

Special Projects Lead

San Francisco, CA · On-site

Oversee data annotation projects, translating complex AI and machine learning requirements into clear workflows and instructions for data annotation teams * Ensure the highest standards of data ...

Abaka AI

Machine Learning Engineer

Mountain View, CA · On-site

... data workflows, including collection, preprocessing, annotation, versioning, and model integration. • Implement and refine training strategies for large-scale AI systems, including vision, video ...

Abaka AI

Machine Learning Engineer

Mountain View, CA · On-site

... data workflows, including collection, preprocessing, annotation, versioning, and model integration. • Implement and refine training strategies for large-scale AI systems, including vision, video ...

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All JobsMachine Learning Data Annotation JobsFull Time Machine Learning Data Annotation JobsFull Time Machine Learning Data Annotation Jobs in Sunnyvale, CA

Full Time Machine Learning Data Annotation information

See Sunnyvale, CA salary details

$44K

$144.1K

$230.6K

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

As of Aug 18, 2026, the average yearly pay for full time machine learning data annotation in Sunnyvale, CA is $144,052.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,600.00 and $159,600.00 per year, depending on experience, location, and employer.

What is a full time machine learning data annotation job?

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 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 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.

What are the most commonly searched types of Machine Learning Data Annotation jobs in Sunnyvale, CA?

The most popular types of Machine Learning Data Annotation jobs in Sunnyvale, CA are:

What are popular job titles related to Full Time Machine Learning Data Annotation jobs in Sunnyvale, CA?

For Full Time Machine Learning Data Annotation jobs in Sunnyvale, CA, the most frequently searched job titles are:

What job categories do people searching Full Time Machine Learning Data Annotation jobs in Sunnyvale, CA look for?

The top searched job categories for Full Time Machine Learning Data Annotation jobs in Sunnyvale, CA are:

What cities near Sunnyvale, CA are hiring for Full Time Machine Learning Data Annotation jobs?

Cities near Sunnyvale, CA with the most Full Time Machine Learning Data Annotation job openings:

Full Time Machine Learning Data Annotation jobs near you
Infographic showing various Full Time Machine Learning Data Annotation job openings in Sunnyvale, CA as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $144,052 per year, or $69.3 per hour.

Data Scientist - Survey Design, Data Annotation, and Machine Learning Evaluation

Apple

Cupertino, CA • On-site

Full-time

Re-posted 28 days ago

Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th 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 experience we deliver is the
result of us making each other's ideas stronger. The diversity of our people and their thinking
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
The Special Projects team at Apple is developing novel user-facing conversational features that
leverage the multimodal capabilities of state-of-the-art foundation models. As part of this
process, we generate real-world and simulated data, gather human data annotations, analyze
the results, and use them to build and evaluate Large Language Model judges. We are looking
for a skilled Data Scientist to join our Machine Learning Evaluations teams. This person will
work closely with ML Engineers to manage and analyze our human and automated data
annotation processes, and to develop, test, and refine LLM judges for generative AI model
evaluation. A successful candidate is experienced in survey design, data annotation, LLM
prompt engineering and prompt optimization, and has strong statistical analysis skills.
Minimum Qualifications
BA or Master's degree in Data Science, Statistics, or a quantitative social science field
2+ years of hands-on experience working in survey design and human data annotation
Proficiency in Python
Excellent communication skills
Preferred Qualifications
PhD in Data Science, Statistics, or a quantitative social science field
Hands-on industry experience with product-focused statistical analysis
Experience working with large-scale multimodal data and data-annotation pipelines
Experience with LLM prompt engineering & prompt optimization
Experience with LLM auto-judges for generative AI model evaluation
A track record of publications or technical presentations in Data Science or a related field
Excellent at cross-functional collaboration

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apple logo

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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