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Annotation Labelling Jobs in Santa Clara, CA (NOW HIRING)

Data Operations Engineer

Mountain View, CA · On-site

$136K - $163K/yr

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

Data Operations Engineer

Mountain View, CA · On-site

$136K - $163K/yr

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

Data Operations Engineer

Mountain View, CA · On-site

$136K - $163K/yr

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

Showing results 21-40

Annotation Labelling information

What is annotation labelling?

Annotation labelling is the process of tagging or marking data—such as images, text, or audio—with relevant information or labels. This is an essential step in preparing datasets for machine learning and artificial intelligence models, as it helps algorithms understand and learn from raw data. Annotation labelling can include tasks like identifying objects in photos, transcribing speech, or categorizing text. Skilled annotators ensure accuracy and consistency to improve model performance. People in this role often use specialized tools or software to streamline and standardize the annotation process.

What are the key skills and qualifications needed to thrive as an annotation labelling specialist?

To thrive as an Annotation Labelling Specialist, you need strong attention to detail, data analysis capabilities, and familiarity with data annotation standards, usually supported by a background in computer science or related fields. Proficiency with annotation tools such as Labelbox, CVAT, or Supervisely, and sometimes knowledge of basic programming or scripting, is typically required. Excellent communication, consistency, and the ability to follow complex instructions are crucial soft skills for producing high-quality labeled data. These skills ensure the accuracy and reliability of datasets, which are foundational for successful machine learning and AI model development.

What are some common challenges faced by annotation labelling professionals, and how can they be managed?

Annotation Labelling professionals often encounter challenges such as maintaining high accuracy while handling repetitive data, meeting tight deadlines, and adapting to evolving project guidelines. To manage these, it’s important to develop strong attention to detail, regularly communicate with team leads to clarify instructions, and leverage annotation tools efficiently. Collaborating closely with quality assurance teams can also help identify and correct errors early, ensuring consistently high-quality outputs.

What is the difference between Annotation Labelling vs Data Labeling Specialist?

AspectAnnotation LabellingData Labeling Specialist
CredentialsBasic technical skills, attention to detailSimilar skills, sometimes additional domain knowledge
Work EnvironmentData annotation platforms, remote or officeData annotation tasks, often remote or in-office
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, healthcare, retail
Search & ComparisonCommonly compared for entry-level data tasksRelated but broader role

Annotation Labelling involves marking data such as images, text, or videos to train AI models. Data Labeling Specialists perform similar tasks but may have a broader scope, including verifying and managing labeled data. Both roles are essential in AI development, often overlapping in skills and work environment, but Annotation Labelling is more focused on the annotation process itself.

What are popular job titles related to Annotation Labelling jobs in Santa Clara, CA? For Annotation Labelling jobs in Santa Clara, CA, the most frequently searched job titles are:
What job categories do people searching Annotation Labelling jobs in Santa Clara, CA look for? The top searched job categories for Annotation Labelling jobs in Santa Clara, CA are:
What cities near Santa Clara, CA are hiring for Annotation Labelling jobs? Cities near Santa Clara, CA with the most Annotation Labelling job openings:

Senior Machine Learning Data Curation Engineer

XPENG

Santa Clara, CA • On-site

$134K - $161K/yr

Full-time

Posted 15 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.