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Full Time Machine Learning Data Annotation Jobs in California

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

... annotation and labeling to support machine learning model training • Document quality standards and create comprehensive reports on data quality metrics • Collaborate with engineering teams to ...

As a 3D Machine Learning Engineer , you will focus on designing, implementing, training, and ... Work closely with the labeling and data operations teams to define robust data annotation ...

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

Data Scientist

Sunnyvale, CA

$181.10K - $318.40K/yr

You will collaborate closely with algorithm engineers, machine learning researchers, QA, annotation ... Description As a Data Scientist focused on Algorithm Evaluation, you will serve as a technical ...

You will collaborate closely with algorithm engineers, machine learning researchers, QA, annotation ... As a Data Scientist focused on Algorithm Evaluation, you will serve as a technical leader ...

What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ... Work closely with the labeling and data operations teams to define robust data annotation ...

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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 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 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 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:
Data Annotation Specialist - South Bay, CA (On Site)

Data Annotation Specialist - South Bay, CA (On Site)

Welo Data

Sunnyvale, CA

Full-time

Posted 15 days ago


Job description

OVERVIEW

Welo Data is looking for a skilled Data Analyst to join our team and contribute to advancing AI technologies. This role offers a unique opportunity to engage directly with cutting-edge AI products, supporting the refinement and performance of machine learning models through precise data analysis and quality assurance.

Project Details
Job Title: Data Analyst
Location: Bay Area, CA (Onsite)
Hours: Full-time, 40 hours per week
Employment Type: W2 Full-Time Employee

Must have valid work authorization in the US (Welocalize does not sponsor VISAs at this time).

This role is an incredible chance to be at the forefront of AI technology, helping shape the future by testing new products, updating machine learning models, and ensuring high-quality data for impactful AI solutions.
Key Responsibilities
  • Test new AI products and provide actionable feedback to improve functionality and user experience.
  • Conduct detailed data annotation and quality assurance of natural language datasets following established guidelines.
  • Collaborate in updating and refining machine learning models to boost accuracy and effectiveness.
  • Analyze data for consistency, relevancy, and alignment with project goals.
  • Perform quality control to identify and report anomalies, error patterns, and discrepancies.
  • Use basic data analysis methods to extract insights and support continuous improvement.
  • Prepare clear and concise reports on findings, including observations on data quality, AI model performance, and user feedback.
Preferred Qualifications
  • University degree in linguistics, translation, or a related field.
  • 3-5 years of professional linguistics experience.
  • Strong analytical skills with the ability to detect patterns and anomalies.
  • Excellent communication skills and the ability to work collaboratively in a fast-paced environment.
  • Adaptability to evolving priorities and project requirements.
Benefits
  • Paid Sick Time & Paid Holiday (combined): 15 days
  • Paid Holidays: Memorial Day and Labor Day
  • Medical Insurance (subject to eligibility requirements)
  • Dental Insurance
  • Vision Insurance
  • Health Savings Account (HSA)
  • Voluntary Life Insurance
  • Accident, Critical Illness, and Hospital Indemnity Insurance
  • Telemedicine Benefit
  • 401(k) Retirement Plan
  • Employee Assistance Program
Please note that in order to verify work authorization as is required by Federal law (I-9 process), all new employees must complete a live video verification with their selected IDs and provide photos of these selected IDs within their first 3 days of employment.

To know more details (Click here)

In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.  In addition, we employ anti-fraud checks to ensure all candidates meet the requirements of the program.


As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.