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Flexible Data Annotation Tech Jobs in California

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

Design and oversee tools or scripts for data validation, annotation accuracy checks, and pipeline ... Flexible working hours Don't meet every single requirement? Studies have shown that women and ...

Cerebras

Client Director, Frontier Data - US

Palo Alto, CA · On-site

$255 - $325/hr

... 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 ...

Voxelcloud

Chief Technology Officer

Los Angeles, CA · On-site

As Voxelcloud's technology moves from early development and validation into full productization ... Optimize annotation data quality and label consistency for R&D in a cost-efficient way. o Work with ...

Voxelcloud

Chief Technology Officer

Los Angeles, CA · On-site

As Voxelcloud's technology moves from early development and validation into full productization ... Optimize annotation data quality and label consistency for R&D in a cost-efficient way. o Work with ...

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All JobsData Annotation Tech JobsFlexible Data Annotation Tech JobsFlexible Data Annotation Tech Jobs in California

Flexible Data Annotation Tech information

Can I do data annotation with no experience?

Data annotation roles often do not require prior experience, as training is typically provided to teach specific labeling tools and guidelines. Basic computer skills and attention to detail are usually sufficient to start, making it accessible for beginners. Over time, developing familiarity with annotation software and understanding data types can improve efficiency and accuracy.

What are some common challenges faced by flexible data annotation techs, and how can they be addressed?

Flexible Data Annotation Techs often encounter challenges such as maintaining consistency across large volumes of data, adapting to evolving project guidelines, and managing tight deadlines. To address these challenges, it's important to establish clear communication with project leads, regularly review annotation protocols, and utilize available training resources. Building strong attention to detail and staying organized can also help ensure high-quality outputs and job satisfaction.

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

AspectFlexible Data Annotation TechData Labeler
CredentialsBasic computer skills, training in annotation toolsBasic education, sometimes specific software training
Work EnvironmentRemote or on-site, tech-focusedPrimarily remote or on-site, data processing settings
Industry UsageAI, machine learning, data scienceAI, machine learning, data preparation
Job FocusApplying labels to datasets using annotation toolsLabeling data according to guidelines

Flexible Data Annotation Tech roles involve using specialized tools to annotate datasets for AI training, often requiring some technical training. Data Labelers focus on applying labels to data, typically with less technical complexity. Both roles are essential in AI development but differ mainly in technical requirements and scope.

What are the key skills and qualifications needed to thrive as a flexible data annotation tech, and why are they important?

To thrive as a Flexible Data Annotation Tech, you need attention to detail, accuracy, and a basic understanding of data labeling or annotation processes, often requiring at least a high school diploma. Familiarity with annotation platforms, data labeling tools, and productivity software is typically necessary, and experience with machine learning datasets can be advantageous. Strong time management, communication, and adaptability help you excel in collaborative and ever-changing project environments. These skills ensure high-quality, consistent data output that directly impacts the performance of AI and machine learning systems.

What is a flexible data annotation tech?

Flexible Data Annotation Tech jobs involve labeling, categorizing, or tagging data—such as images, text, audio, or video—to help train machine learning models. These roles are often remote or offer flexible schedules, making them appealing for those seeking adaptable work hours. Tasks can include identifying objects in photos, transcribing audio, or sorting information based on specific guidelines. The work is essential for improving the accuracy of artificial intelligence systems by providing them with high-quality annotated data. No advanced technical skills are usually required, but attention to detail and reliability are important.
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 Flexible Data Annotation Tech jobs in California? For Flexible Data Annotation Tech jobs in California, the most frequently searched job titles are:
What job categories do people searching Flexible Data Annotation Tech jobs in California look for? The top searched job categories for Flexible Data Annotation Tech jobs in California are:
What cities in California are hiring for Flexible Data Annotation Tech jobs? Cities in California with the most Flexible Data Annotation Tech job openings:
Flexible Data Annotation Tech jobs near you
Infographic showing various Flexible Data Annotation Tech job openings in California as of August 2026, with employment types broken down into 1% As Needed, 68% Full Time, 27% Part Time, 2% Temporary, and 2% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution.

Senior Machine Learning Data Curation Engineer

XPENG

Santa Clara, CA • On-site

$134K - $161K/yr

Full-time

Posted 19 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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