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Full Time Machine Learning Data Annotation Jobs in California

Welocalize, Inc.

Data Quality Lead

San Francisco, CA · On-site

Stay updated with the latest in machine learning, data annotation, and natural language processing. * Address complex technical challenges faced by the team. * Provide guidance on advanced annotation ...

Welocalize, Inc.

Data Quality Lead

San Francisco, CA

Stay updated with the latest in machine learning, data annotation, and natural language processing. * Address complex technical challenges faced by the team. * Provide guidance on advanced annotation ...

Sunday Inc

Data Annotation Lead

Redwood City, CA · On-site

You'll work in coordination with Machine Learning, Software engineering, and Data to define the framework and tools on which to build a data annotation team around. Your role is vital to ensuring our ...

Welocalize, Inc.

Data Quality Lead

San Francisco, CA

Stay updated with the latest in machine learning, data annotation, and natural language processing. * Address complex technical challenges faced by the team. * Provide guidance on advanced annotation ...

Welocalize, Inc.

Data Labeling Associate

San Diego, CA

$17 - $22/hr

The ideal candidate will have a foundational understanding of machine learning, data annotation ... other full-time employees. * Handle data efficiently, ensuring its integrity throughout the ...

Welocalize, Inc.

Data Quality Analyst

New York, NY

The ideal candidate will have a foundational understanding of machine learning, data annotation ... other full-time employees. * Handle data efficiently, ensuring its integrity throughout the ...

Encord

Human Data Operations Strategist

San Francisco, CA · On-site

$150K - $230K/yr

Oversee data annotation projects, translating complex AI and machine learning requirements into clear workflows and instructions for data annotation teams * Ensure the highest standards of data ...

Encord

Human Data Operations Strategist

San Francisco, CA · On-site

$150K - $230K/yr

Oversee data annotation projects, translating complex AI and machine learning requirements into clear workflows and instructions for data annotation teams * Ensure the highest standards of data ...

Abaka AI

Machine Learning Engineer

Mountain View, CA · On-site

... data workflows, including collection, preprocessing, annotation, versioning, and model integration. • Implement and refine training strategies for large-scale AI systems, including vision, video ...

Abaka AI

Machine Learning Engineer

Mountain View, CA · On-site

... data workflows, including collection, preprocessing, annotation, versioning, and model integration. • Implement and refine training strategies for large-scale AI systems, including vision, video ...

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a ... Coordinate data collection and annotation efforts. * Work with real-time data and content coming ...

NTENT

Machine Learning Engineer

Carlsbad, CA

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a ... Coordinate data collection and annotation efforts. * Work with real-time data and content coming ...

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All JobsFull Time Machine Learning Data Annotation JobsFull Time Machine Learning Data Annotation Jobs in California

Full Time Machine Learning Data Annotation information

What are the key skills and qualifications needed to thrive as a Full Time Machine Learning Data Annotation Specialist, and why are they important?

To thrive as a Full Time Machine Learning Data Annotation Specialist, you need strong attention to detail, basic data literacy, and familiarity with data labeling concepts, often supported by a high school diploma or equivalent. Proficiency in specialized annotation platforms, spreadsheet tools, and sometimes knowledge of Python or labeling frameworks is typically required. Reliability, patience, and effective communication are valuable soft skills for ensuring accuracy and collaborating with team members. These skills and qualities are crucial because they directly impact the quality of training data, which is essential for developing effective machine learning models.

What are Full Time Machine Learning Data Annotation jobs?

Full time machine learning data annotation jobs involve labeling, tagging, or categorizing data such as images, text, audio, or video to help train machine learning models. Data annotators play a crucial role in ensuring that AI systems learn from high-quality, accurately labeled datasets. These positions often require attention to detail, consistency, and sometimes familiarity with the subject matter or specialized tools. Full-time roles may be remote or onsite and can span industries like autonomous vehicles, healthcare, retail, and more.

What are some common challenges faced by machine learning data annotators, and how are these typically addressed within a team?

Machine learning data annotators often encounter challenges such as maintaining consistency in labeling, handling ambiguous data, and meeting tight deadlines for large datasets. Teams usually address these by establishing clear annotation guidelines, conducting regular training sessions, and implementing quality assurance processes like peer reviews and spot checks. Collaboration with data scientists and project managers is also common, ensuring that annotators can ask questions and clarify uncertainties, leading to higher-quality labeled data and a supportive work environment.

What is the difference between Full Time Machine Learning Data Annotation vs Data Labeling Specialist?

AspectFull Time Machine Learning Data AnnotationData Labeling Specialist
CredentialsHigh school diploma or equivalent; some roles prefer technical certificationsHigh school diploma or equivalent; training often provided on the job
Work EnvironmentOffice or remote; collaborative with data science teamsRemote or office; focused on labeling tasks
Industry UsageUsed across AI/ML companies, tech firms, and startupsCommon in AI/ML, data services, and outsourcing companies
Job FocusCreating labeled datasets for machine learning modelsAnnotating data such as images, videos, or text for AI training

Full Time Machine Learning Data Annotation involves creating high-quality labeled datasets for AI models, often requiring technical understanding. Data Labeling Specialists focus on annotating data accurately, typically with less emphasis on technical skills. Both roles are essential in AI development but differ mainly in scope and technical complexity.

What are the most commonly searched types of Machine Learning Data Annotation jobs in California? The most popular types of Machine Learning Data Annotation jobs in California are:
What are popular job titles related to Full Time Machine Learning Data Annotation jobs in California? For Full Time Machine Learning Data Annotation jobs in California, the most frequently searched job titles are:
What job categories do people searching Full Time Machine Learning Data Annotation jobs in California look for? The top searched job categories for Full Time Machine Learning Data Annotation jobs in California are:
What cities in California are hiring for Full Time Machine Learning Data Annotation jobs? Cities in California with the most Full Time Machine Learning Data Annotation job openings:
Full Time Machine Learning Data Annotation jobs near you
Data Quality Lead

Data Quality Lead

Welocalize, Inc.

San Francisco, CA • On-site

Full-time

Posted 4 days ago

Welocalize rating

5.9

Company rating: 5.9 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

335th of 428 rated business services

Job description

If you have a Candidate Login already, but have forgotten your password please use the steps to reset your password. If you have forgotten your email login, please contact servicedesk@welocalize.com subject Workday Candidate Login
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Job Responsibilities:
The ideal candidate will possess both technical prowess in machine learning and natural language processing, along with strong leadership skills to guide and mentor their team.
Key Responsibilities:
Team Leadership and Management:
  • Lead, mentor, and grow a team of data annotators and quality analysts.
  • Ensure team members are trained, informed, and adhere to company standards and best practices.
  • Oversee team performance, set goals, and conduct regular evaluations.

Strategic Oversight:
  • Collaborate with senior management to define strategic goals and deliverables.
  • Allocate resources and tasks efficiently among team members.
  • Act as a bridge between the annotation team and other departments, ensuring effective communication.

Quality Assurance and Analysis:
  • Oversee quality assurance processes and set benchmarks for performance and accuracy.
  • Review and approve detailed reports on findings prepared by team members.
  • Drive continuous improvement initiatives within the team based on analytics and performance metrics.

Technical Expertise:
  • Stay updated with the latest in machine learning, data annotation, and natural language processing.
  • Address complex technical challenges faced by the team.
  • Provide guidance on advanced annotation techniques and quality analysis.

Linguistic and NLP Leadership:
  • Guide the team in applying best practices in NLP and linguistics.
  • Ensure consistent linguistic accuracy across all processed and annotated data.

Education: Bachelor's degree in Computer Science, Data Science, Linguistics or Computational Linguistics or a related field.
Experience:
  • Prior experience in a leadership role within a data annotation or machine learning team.
  • Proven track record of team management, mentorship, and performance optimization.
  • Strong analytical skills with the ability to derive actionable insights from data.
  • Deep understanding of machine learning models, data annotation, and quality assurance.
  • Excellent communication and interpersonal skills.

Additional Job Details:
Additional Information:
This role primarily focuses on English US data sets; however, having experience with translation or multi-lingual data sets can be advantageous.

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