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Data Annotation Tech Jobs in Pleasanton, CA (NOW HIRING)

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 ...

Turing

Client Director, Frontier Data - US

Palo Alto, CA · On-site

$255K - $325K/yr

... team includes AI technologists from Meta, Google, Microsoft, Apple, Amazon, McKinsey, Bain ... Design and oversee tools or scripts for data validation, annotation accuracy checks, and pipeline ...

Tapestry

Data Science Manager

Mountain View, CA · On-site

Annotation Rigor: Drive a comprehensive and scalable data annotation strategy that prioritizes ... PhD or Master's in a quantitative field and 8+ years of tech or energy industry work experience as ...

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Showing results 21-40

All JobsData Annotation Tech JobsData Annotation Tech Jobs in Pleasanton, CA

Data Annotation Tech information

See Pleasanton, CA salary details

$13

$25

$38

How much do data annotation tech jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for data annotation tech in Pleasanton, CA is $25.42, according to ZipRecruiter salary data. Most workers in this role earn between $18.75 and $30.24 per hour, depending on experience, location, and employer.

How to become a data annotation tech?

To become a data annotation tech, you typically need a high school diploma or equivalent, strong attention to detail, and familiarity with data labeling tools or software. Some roles may require basic knowledge of machine learning concepts or specific platforms like Labelbox or CVAT. Gaining experience through online courses or tutorials can also improve job prospects.

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

To thrive as a Data Annotation Tech, you need keen attention to detail, basic computer literacy, and familiarity with data labeling standards, often supported by a high school diploma or equivalent. Experience with annotation platforms, image or text labeling tools, and basic knowledge of data management systems is highly valuable. Strong organizational skills, patience, and effective communication set top candidates apart in this field. These skills and qualities ensure annotated data is accurate, consistent, and valuable for machine learning or AI projects.

What does a data annotation tech do?

A typical day as a Data Annotation Tech involves reviewing large sets of data—such as images, text, or audio—and accurately labeling or categorizing them using specialized software. You may work independently or as part of a team, following specific project guidelines to ensure data integrity and consistency. Collaboration with project managers or data scientists is common when clarifying ambiguous data points or addressing annotation challenges. Additionally, productivity targets and quality checks are a regular part of the workflow, helping to keep projects on schedule and maintain high standards.

Does data annotation actually pay you?

Data annotation jobs typically pay hourly or per task, with rates varying depending on the platform and complexity of the work. Many companies and platforms offer remote opportunities that provide consistent payment once tasks are completed, often requiring basic skills in data labeling tools. Payment is generally reliable for those who meet quality standards and adhere to deadlines.

What is a data annotation tech?

A Data Annotation Tech is responsible for labeling and categorizing data, such as text, images, audio, or video, to train machine learning models. They follow specific guidelines to ensure accuracy and consistency in annotations, which helps improve the performance of AI systems. This role often involves repetitive tasks, attention to detail, and familiarity with various annotation tools. Data annotation is crucial for AI development in industries like healthcare, finance, and autonomous driving.

How much do data annotation technicians make?

Data annotation technicians typically earn between $12 and $20 per hour, depending on experience, location, and the complexity of the tasks. Many roles are entry-level and may offer flexible schedules or remote work opportunities.
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Data Annotation Tech jobs near you
Infographic showing various Data Annotation Tech job openings in Pleasanton, CA as of July 2026, with employment types broken down into 1% As Needed, 78% Full Time, 18% Part Time, 1% Temporary, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $52,876 per year, or $25.4 per hour.

Senior Machine Learning Data Curation Engineer

XPENG

Santa Clara, CA • On-site

$134K - $161K/yr

Other

Posted 14 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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