ZipRecruiter

Log In

1

Annotation Labelling Jobs in Sunnyvale, CA (NOW HIRING)

Abaka AI

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. • ...

Aerotek

Data Labeling Specialist

San Jose, CA

$30/hr

Use annotation software to label objects, body positions, and interactions. * Identify unusual or unclear situations and flag them for review. * Complete large volumes of annotation work while ...

Abaka AI

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. • ...

Aerotek

Data Labeling Specialist

San Jose, CA

$30/hr

Use annotation software to label objects, body positions, and interactions. * Identify unusual or unclear situations and flag them for review. * Complete large volumes of annotation work while ...

previous page

Showing results 41-60

All JobsAnnotation Labelling JobsAnnotation Labelling Jobs in Sunnyvale, CA

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 Sunnyvale, CA?

For Annotation Labelling jobs in Sunnyvale, CA, the most frequently searched job titles are:

What job categories do people searching Annotation Labelling jobs in Sunnyvale, CA look for?

The top searched job categories for Annotation Labelling jobs in Sunnyvale, CA are:

What cities near Sunnyvale, CA are hiring for Annotation Labelling jobs?

Cities near Sunnyvale, CA with the most Annotation Labelling job openings:

Annotation Labelling jobs near you
Infographic showing various Annotation Labelling job openings in Sunnyvale, CA as of August 2026, with employment types broken down into 1% As Needed, 45% Full Time, 50% Part Time, and 4% Contract. Highlights an 48% Physical, 1% Hybrid, and 51% Remote job distribution.

Data Operations Engineer

Abaka AI

Mountain View, CA • On-site

$136K - $163K/yr

Full-time

Re-posted 26 days ago

Job description

Job Summary:
Abaka AI is built on one mission: to be the world’s most trusted data partner for AI companies. They are seeking a Data Operations Engineer to own and operate the internal dataset library, ensuring fast, accurate, and scalable access to data while coordinating with engineering, product, and business teams.
Responsibilities:
• Develop and maintain a comprehensive understanding of Abaka AI’s dataset library, including data structure, quality, and applicable use cases across modalities (text, image, video, audio, 3D).
• Serve as the internal point of contact for dataset-related inquiries, providing clear and timely responses to questions from engineering, product, and business teams.
• Translate ambiguous or high-level requests into concrete dataset solutions, identifying appropriate data sources or gaps.
• Inspect and validate datasets for quality, completeness, and consistency using SQL, Python, or other tools as needed.
• Coordinate with global data teams, including teams in China, to resolve data issues, clarify requirements, and ensure timely delivery without unnecessary escalation.
• Maintain and improve internal documentation, organization, and accessibility of datasets.
• Identify inefficiencies in current workflows and propose improvements to systems, tooling, and processes that support dataset management and usage.
• Support cross-functional initiatives by providing dataset insights, technical context, and operational guidance.
Qualifications:
Required:
• Bachelor’s degree in Computer Science, Data Engineering, or a related field, or equivalent practical experience.
• 1–4 years of experience in data operations, data engineering, or a related role involving direct interaction with datasets.
• Professional proficiency in Mandarin Chinese and English is required, as this role involves frequent collaboration with China-based vendors and external partners.
• Strong problem-solving skills and ability to operate effectively in ambiguous, fast-paced environments.
• Proficiency in SQL and/or Python for data inspection, validation, and basic analysis.
• Experience working with real-world datasets, including handling data quality issues, inconsistencies, and edge cases.
• Strong communication skills, with the ability to work across technical and non-technical teams.
• High level of ownership and accountability, with the ability to manage multiple requests and priorities simultaneously.
Preferred:
• Experience with multimodal datasets (text, image, video, audio, or 3D).
• Familiarity with data annotation, labeling workflows, or dataset preparation for machine learning.
• Experience working with international teams, particularly in cross-border environments.
• Exposure to AI/ML workflows, including training, fine-tuning, or evaluation datasets.
Company:
Abaka AI provides accurate and efficient AI data services, including data collection, data cleaning, data annotation, and OTS datasets. Founded in 2021, the company is headquartered in Palo Alto, USA, with a team of 51-200 employees. The company is currently Growth Stage.

Apply