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Full Time Machine Learning Data Annotation Jobs in California

campus4tech

Technical Program Manager III

Mountain View, CA · On-site

$152.20K - $197K/yr

... annotation programs that power our cutting-edge AI research initiatives. This role sits at the ... Computer Science, Data Science, Machine Learning, Information Systems) or equivalent practical ...

Abaka AI

Data Operations Engineer

Mountain View, CA · On-site

$136.30K - $163.60K/yr

Preferred : • Experience with multimodal datasets (text, image, video, audio, or 3D). • Familiarity with data annotation, labeling workflows, or dataset preparation for machine learning. • ...

Sesame

Technical Program Manager, Data

San Francisco, CA · On-site

$200K - $260K/yr

... machine learning researchers and engineers. * Proven experience leading data labeling projects ... Experience managing full-time employees or contractors involved in data labeling. * Expertise in ...

Apple

ML Data Program Manager, MLO

Cupertino, CA · On-site

Do you believe Machine Learning and AI can change the world? We truly believe it can! We are the ... Our MLO Data team focuses on data acquisition, data synthesis, data science, annotation, and data ...

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Full Time Machine Learning Data Annotation information

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 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 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 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 California? The most popular types of Machine Learning Data Annotation jobs in California are:
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Full Time Machine Learning Data Annotation jobs near you
Generative AI Analyst (Chinese zh-CN) - Onsite \u007C San Jose, CA

Generative AI Analyst (Chinese zh-CN) - Onsite \u007C San Jose, CA

Welo Data

Santa Clara, CA

$136.80K/yr

Full-time

Posted 16 days ago

Job description

About the Role

We are looking for highly detail-oriented Generative AI Analysts to join our team onsite in San Jose, California. In this role, you will contribute to the development of cutting-edge AI technologies by supporting the annotation, evaluation, and quality review of multilingual and multimodal datasets used to train generative AI systems.

This position is ideal for candidates passionate about AI, language, data quality, and emerging technologies, with strong analytical skills and native-level Chinese proficiency.

What You’ll Do
  • Perform annotation and labeling tasks for Chinese generative AI datasets, including text, image, video, audio, and multimodal content
  • Review and evaluate AI-generated prompts and responses across a variety of topics and use cases
  • Conduct quality assurance checks to ensure accuracy, consistency, and compliance with annotation guidelines
  • Identify edge cases, inconsistencies, and quality issues in datasets and model outputs
  • Support data categorization, tagging, evaluation, and content review workflows for machine learning systems
  • Assist in the creation and refinement of annotation guidelines and evaluation frameworks
  • Collaborate with cross-functional teams to improve operational processes and annotation quality
  • Provide feedback on tools, workflows, and annotation methodologies
Requirements
  • Native-level proficiency in Chinese and strong English communication skills (written and verbal)
  • Excellent attention to detail and ability to follow complex guidelines and processes
  • Strong interest in generative AI, machine learning, and emerging technologies
  • Previous experience in data annotation, content review, quality assurance, or labeling operations is preferred
  • Bachelor’s degree or equivalent practical experience
  • Experience or academic background in Finance, STEM, Legal, Medical, Coding, or other specialized fields is highly valued.
  • Ability to work onsite full-time in San Jose, CA
Ways to Stand Out from the Crowd
  • Familiarity with generative AI systems, LLMs, RLHF, or multimodal AI workflows
  • Experience evaluating prompts, responses, images, videos, or AI training datasets
  • QA/testing experience within AI, data operations, or content moderation environments
  • Experience with taxonomy creation, evaluation rubrics, or dataset quality initiatives
  • Python or scripting knowledge
  • Additional language proficiency is a plus (Korean, Japanese, Mandarin, Spanish, German, French, etc.)
Please note that in order to verify work authorization as is required by Federal law (I-9 process), all new employees must complete a live video verification with their selected IDs and provide photos of these selected IDs within their first 3 days of employment.
 
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In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.  In addition, we employ anti-fraud checks to ensure all candidates meet the requirements of the program.
 
 
As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com
 
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.