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Intern Data Annotation Tech Jobs in California (NOW HIRING)

Sesame

Technical Program Manager, Data

San Francisco, CA · On-site

$200K - $260K/yr

... annotation pipelines. Preferred Qualifications: * Understanding of ML data pipelines and their applications. * Experience working with LLMs. * Familiarity with data labeling for audio technologies ...

campus4tech

Technical Program Manager III

Mountain View, CA · On-site

$152K - $197K/yr

Strong understanding of ML development workflows, data pipelines, and annotation lifecycle ... Preferred good working knowledge of GPU technology and its applications in generative AI and ...

General Motors

Staff ML Systems Engineer

Sunnyvale, CA · On-site

... data-annotation pipelines and machine-led training data solutions at foundation-model scale . We ... Driven to learn new technologies and deepen your expertise across frontend, backend, and data/ML ...

General Motors

Staff ML Systems Engineer

Sunnyvale, CA · On-site

... data-annotation pipelines and machine-led training data solutions at foundation-model scale . We ... Driven to learn new technologies and deepen your expertise across frontend, backend, and data/ML ...

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All JobsIntern Data Annotation Tech JobsIntern Data Annotation Tech Jobs in California

Intern Data Annotation Tech information

What is an intern data annotation tech?

Intern Data Annotation Techs are entry-level professionals, often students or recent graduates, who support machine learning projects by labeling and categorizing data, such as images, text, or audio. Their work is essential for training AI systems, as accurately annotated data helps algorithms learn to make correct predictions. These interns typically use specialized software tools to tag or classify data according to specific guidelines. The role requires attention to detail, consistency, and sometimes basic technical skills, depending on the complexity of the data and tasks. Internships in data annotation can provide valuable exposure to the fields of artificial intelligence and data science.

What are the key skills and qualifications needed to thrive as an intern data annotation tech?

To thrive as an Intern Data Annotation Tech, you need attention to detail, basic data management skills, and familiarity with data labeling concepts, often supported by a high school diploma or ongoing college coursework. Experience with annotation platforms, spreadsheet tools, and sometimes basic scripting languages is helpful. Strong communication, reliability, and the ability to follow detailed instructions are valuable soft skills in this role. These abilities ensure accurate and efficient data labeling, which is critical for training reliable machine learning models.

What are some common challenges faced by intern data annotation techs, and how can they overcome them?

Intern Data Annotation Techs often encounter challenges such as maintaining consistency in labeling large datasets and understanding nuanced instructions for annotation tasks. To overcome these hurdles, it's important to ask clarifying questions early on, regularly review annotation guidelines, and participate in team discussions about edge cases. Collaboration with more experienced annotators and feedback from supervisors also help in refining skills and ensuring high-quality data preparation. Developing attention to detail and adaptability will contribute to a successful internship experience.

What is the difference between Intern Data Annotation Tech vs Intern Data Labeler?

AspectIntern Data Annotation TechIntern Data Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentData annotation platforms, remote or officeData labeling platforms, remote or office
Industry UsageAI, machine learning, data scienceAI, machine learning, data science
Job FocusAnnotating data for training AI modelsLabeling data for machine learning algorithms

Both roles involve preparing data for AI systems, with similar skills and work environments. The main difference lies in terminology; 'Data Annotation Tech' emphasizes technical annotation tasks, while 'Data Labeler' is a more general term. Both are entry-level positions vital for training AI models in the tech industry.

Can I do data annotation with no experience?

Intern Data Annotation Tech roles often do not require prior experience, as training is typically provided to teach skills like image or text labeling using annotation tools. Basic computer skills and attention to detail are usually sufficient to start, making it accessible for beginners. Developing familiarity with annotation software and understanding data quality standards can improve job performance over time.

Does data annotation tech actually pay?

Data annotation technicians are paid for their work, with wages typically ranging from minimum wage to higher rates depending on experience, complexity of tasks, and the employer. Payment is usually hourly or per task, and some roles may require basic skills in data labeling tools or software. Compensation varies by company and location but generally provides a reliable income for entry-level positions.

Is it hard to get hired for data annotation?

Getting hired as a data annotation intern typically requires basic computer skills, attention to detail, and sometimes familiarity with annotation tools. Many positions are entry-level and may not require extensive experience, making the application process relatively accessible for beginners. However, competition can vary depending on the company and location.

What are the most commonly searched types of Data Annotation Tech jobs in California?

The most popular types of Data Annotation Tech jobs in California are:

What are popular job titles related to Intern Data Annotation Tech jobs in California?

For Intern Data Annotation Tech jobs in California, the most frequently searched job titles are:

What job categories do people searching Intern Data Annotation Tech jobs in California look for?

The top searched job categories for Intern Data Annotation Tech jobs in California are:

What cities in California are hiring for Intern Data Annotation Tech jobs?

Cities in California with the most Intern Data Annotation Tech job openings:

Intern Data Annotation Tech jobs near you
Infographic showing various Intern Data Annotation Tech job openings in California as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Senior Machine Learning Data Curation Engineer

XPENG

Santa Clara, CA

$134K - $161K/yr

Full-time

Posted 29 days ago

Job description

XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing (eVTOL) aircraft, and robotics. With a strong focus on intelligent mobility, XPENG is dedicated to reshaping the future of transportation through cutting-edge R&D in AI, machine learning, and smart connectivity.
 
We are seeking a Machine Learning Data Curation Engineer to spearhead the data pipeline development and dataset management for our core AI initiatives. You will bridge the gap between raw data and robust, high-performance machine learning models by designing intelligent tools for data collection, cleaning, and annotation.
 
Key Responsibilities:
  • Dataset Lifecycle Management: Oversee the collection, organizing, cleaning, and maintenance of large-scale, high-quality datasets for model training.
  • Pipeline Development: Build and maintain scalable data processing pipelines and automated intelligent agents to continuously ingest, clean, and enrich training data.
  • Quality & Benchmarking: Define, track, and optimize dataset quality metrics (e.g., diversity, absence of bias) to directly improve ML model performance.
  • Annotation & Labeling: Design and manage data annotation workflows, collaborating with domain experts to ensure clear, accurate classification protocols.
  • Governance & Compliance: Maintain data provenance, ensure compliance with data governance policies (e.g., GDPR, HIPAA if applicable), and enforce data security measures.
 
Qualifications:
  • Education: Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a highly quantitative field.
  • Technical Skills:
    • Proficiency in programming languages like Python or SQL.
    • Experience with Big Data tools and cloud platforms (e.g., AWS, GCP, BigQuery).
    • Familiarity with ML frameworks (e.g., PyTorch, Hugging Face).
  • Experience: 3+ years managing large-scale datasets, developing data curation heuristics, and working alongside ML researchers or data scientists.
  • Analytical Mindset: Strong problem-solving skills to identify data quality anomalies, address model biases, and establish evaluation frameworks.
 
What do we provide:
  • A fun, supportive and engaging environment.
  • Infrastructures and computational resources to support your work.
  • Opportunity to work on cutting edge technologies with the top talents in the field.
  • Opportunity to make a significant impact on the transportation revolution by the means of advancing autonomous driving.
  • Competitive compensation package.
  • Snacks, lunches, dinners, and fun activities.
 
The base salary range for this full-time position is $174,720 - $295,680, in addition to bonus, equity and benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
 
We are an Equal Opportunity Employer. It is our policy to provide equal employment opportunities to all qualified persons without regard to race, age, color, sex, sexual orientation, religion, national origin, disability, veteran status or marital status or any other prescribed category set forth in federal or state regulations.

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