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Annotation Labelling Jobs (NOW HIRING)

GE HealthCare

Data Manager - AI Development

$94K - $141K/yr

Track data collection and annotation budget. 3. Annotation & Labeling Oversight * Coordinate data annotation activities with internal teams and external vendors. * Track annotation progress ...

Welocalize

Data Labeling Associate

Washington, DC

$34/hr

WHAT YOU'LL DO • Execute Data labelling and annotation tasks across speech and voice datasets. • Work with audio and language data, including transcription, categorization, and tagging. YOU ARE A ...

Welocalize

Data Labeling Associate

New York, NY

$34/hr

WHAT YOU'LL DO • Execute Data labelling and annotation tasks across speech and voice datasets. • Work with audio and language data, including transcription, categorization, and tagging. YOU ARE A ...

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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, and why are they important?

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.

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Annotation Labelling jobs near you
Infographic showing various Annotation Labelling job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 56% Full Time, 12% Part Time, 1% Temporary, and 30% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution.
Senior/Staff Software Engineer, ML Data Infrastructure

Senior/Staff Software Engineer, ML Data Infrastructure

Nuro

Mountain View, CA • On-site

$126K - $171K/yr

Full-time

Posted 26 days ago

Job description

Job Summary:
Nuro is a self-driving technology company on a mission to make autonomy accessible to all. They are seeking a Senior/Staff Software Engineer to design and develop scalable data infrastructure for machine learning applications in autonomous driving, focusing on data pipelines, storage systems, and evaluation metrics.
Responsibilities:
• Design and develop unified, introspectable, large-scale batch and streaming data pipelines that can ingest and process data across a wide range of use cases relevant to evaluation.
• Create and implement a storage system capable of accommodating both the large volume and diverse range of evaluation and performance metrics.
• Construct intuitive dashboards and reports to present evaluation results, facilitating straightforward comparisons that highlight both improvements and regressions of the ML components and the overall system.
• Develop and maintain continuous testing and monitoring systems to guarantee the integrity and resilience of our data and associated data pipelines.
• Develop data mining tools with applied ML techniques to support data discovery needs from Autonomy including Perception, Behavior, and Mapping
• Develop data annotation tools to support first-party and third-party labeling workforce to provide high fidelity perception, mapping, and driving trajectory labels
• Scale data annotation labels with applied State-of-the-art ML techniques
Qualifications:
Required:
• You have a degree in BS, MS.c or Ph.D, plus 4 years of relevant work experience
• Strong proficiency in Python or similar languages
• Domain experience: Experience working with large-scale data and building scalable & reliable systems/data pipelines; ability to understand and design complex systems
• Engineering leadership: Experience setting team or project product and technical vision, timelines, and prioritization; being a Technical Lead, mentoring and support junior engineers
• Technical excellence: Ability and willingness to deep dive into implementation, driving technical standards and best practices across broader software organization
• A bachelor's degree in Computer Science, Electrical Engineering, or a closely related field
Preferred:
• Strong proficiency in C++ or other high-performance low-level languages
• Strong knowledge of GCP, GCS, BigQuery, or PostgreSQL
• Knowledge of data engineering, and its tooling and best practices
• Knowledge of batch and streaming data processing, warehousing, and analytics solutions
• Experience working with large-scale distributed data systems
• Experience with system & framework design
• Experience with data workflow orchestration platforms
Company:
Nuro is a robotics company specializing in the development of autonomous driving technologies. Founded in 2016, the company is headquartered in Mountain View, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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