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Full Time Machine Learning Data Annotation Jobs in California

Human Archive

Machine Learning Engineer

San Francisco, CA · On-site

$100K - $150K/yr

The Opportunity As a Machine Learning Engineer, you'll work on multimodal perception, VLA training ... annotation, dataset QA, and robotics evaluation * Publish research on multimodal data by fine ...

campus4tech

Technical Program Manager III

Mountain View, CA · On-site

$152K - $197K/yr

... annotation programs that power our cutting-edge AI research initiatives. This role sits at the ... Computer Science, Data Science, Machine Learning, Information Systems) or equivalent practical ...

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. • ...

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. • ...

Apple

Machine Learning - Data Scientist Lead

Sunnyvale, CA · On-site

$184K - $324K/yr

The Video Engineering Data Analytics and Quality group is looking for a technical lead with deep expertise in evaluating machine learning and deep learning models, including foundation models and ...

Atoms

Machine Learning Engineer

Mountain View, CA · On-site

Familiarity with Java/Go • Experience with data analysis and visualization • Strong ... Machine Learning, Data Mining, Statistics, or related technical field with preferred 3+ years of ...

Atoms

Machine Learning Engineer

Mountain View, CA · On-site

Familiarity with Java/Go • Experience with data analysis and visualization • Strong ... Machine Learning, Data Mining, Statistics, or related technical field with preferred 3+ years of ...

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. • ...

Sesame

Technical Program Manager, Data

San Francisco, CA · On-site

$200K - $260K/yr

... machine learning researchers and engineers. * Proven experience leading data labeling projects ... Experience managing full-time employees or contractors involved in data labeling. * Expertise in ...

Apple

Algorithm Evaluation Manager

Sunnyvale, CA · On-site

Familiarity with the design and architecture of machine learning inference pipelines and underlying infrastructure. Data & Annotation: Hands-on experience designing and managing data curation ...

Mercor

Chief Data Scientist

San Francisco, CA · Remote

$70 - $100/hr

... applied machine learning . * Ability to commit to 40 hours per week during weekdays for the ... Prior experience with data annotation , labeling, evaluation, or human feedback collection.

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All JobsMachine Learning Data Annotation 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 Annotator / Geospatial Annotation Specialist

Data Annotator / Geospatial Annotation Specialist

Aechelon Technology

South San Francisco, CA • On-site

$82K - $92K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 19 days ago

Job description

Aechelon Technology, Inc. is a leading producer of 3D simulator content, including Geospecific visual/sensor databases and realistic 3D models. We seek people who share our passion for real-time computer graphics and commitment to our mission of helping make our Nation's pilots safer. We will give you a chance to work with some of the most talented people in the graphics industry.
The Data Annotator / Geospatial Annotation Specialist plays a critical role in the creation of high-quality training datasets used to develop and refine Aechelon's machine learning and computer vision models. This role supports both the Advanced Model Development Group and the Applied Real-Time Vision Group, ensuring datasets for object detection, segmentation, and classification are accurate, consistent, and production-ready.
The Specialist performs detailed vector annotation, image segmentation, and dataset preparation while adhering to strict quality standards. Because model performance is highly dependent on high-quality annotation, this role requires exceptional attention to detail and a strong understanding of geospatial imagery.
In addition to dataset creation, the Specialist will learn core machine learning concepts and gain experience operating inference tools and models within the DAML pipeline, becoming a direct contributor to model evaluation and workflow improvements.
Key Responsibilities
  • Create precise vector annotations and segmentation masks for training computer vision and object detection models.
  • Perform detailed image segmentation, manually labeling features across large and varied imagery datasets.
  • Follow established annotation guidelines and maintain consistency across global AOIs.
  • Validate and refine automated detection outputs; correct errors or incomplete detections.
  • Work with ML team to understand annotation needs, edge cases, and quality thresholds.
  • Learn how to operate model inference tools and assist in evaluating model performance.
  • Provide feedback on false positives/negatives, detection weaknesses, and annotation ambiguities.
  • Maintain structured documentation of annotation processes, datasets, feature definitions, and QA results.
  • Support improvements to dataset pipelines and annotation workflows through iterative refinement and testing.
  • Assist multiple DAML groups as needed, depending on dataset demands and model development cycles.
Required Qualifications
  • Background in GIS, Remote Sensing, Image Analysis, Digital Art, Photography, or related field (degree preferred but not required with strong experience).
  • Prior experience with image annotation, data labeling, GIS feature extraction, or segmentation workflows.
  • Ability to visually identify subtle features in imagery with extreme precision.
  • Strong analytical, organizational, and documentation skills.
  • Ability to work with large datasets for extended periods while maintaining accuracy and focus.
Required Skills and Tools
  • Adobe Photoshop (Advanced): Expertise in mask creation, polygon tracing, color differentiation, clean-up workflows, and segmentation editing.
  • GIS Tools (Intermediate+): Ability to work in QGIS, ERDAS Imagine, or Global Mapper for spatial visualization and annotation support.
  • Geospatial Data Handling: Ability to work with shapefiles, GeoPackages, raster datasets, and other formats used in ML workflows.
  • Python (Basic-Intermediate): Ability to run scripts, perform data checks, and assist with pre-processing tasks.
  • Documentation Tools: Proficiency using Jupyter Notebook and Git for tracking annotation notes and revisions.

Strongly Desired Skills and Tools
  • Experience creating training datasets for machine learning, object detection, or image segmentation models.
  • Familiarity with YOLO, PyTorch, or fast.ai (conceptual knowledge acceptable).
  • Ability to create simple scripts to automate annotation steps or pre-processing tasks.
  • Experience using ChatGPT or other LLMs to improve workflows, generate helper scripts, or automate documentation.
  • Understanding of geospatial features such as vegetation, buildings, vehicles, aircraft, or other runtime elements.
Reporting Expectations
The Specialist reports jointly to managers in the Advanced Model Development and Applied Real-Time Vision groups depending on project assignment. Regular updates are expected on dataset progress, annotation quality, workflow blockers, and model evaluation findings. The Specialist is expected to meet annotation quotas while maintaining strict accuracy and quality standards.
Compensation
$82,000 - 92,000 / year
The above range is specific to CALIFORNIA and may not be applicable to other locations. Final compensation is based on factors such as the candidate's skills, qualifications, and experience.
We offer a very attractive compensation package including competitive base salary, company performance-based profit sharing, 401k, 100% employer paid health benefits (medical, dental, vision, life, std, ltd, and life insurance plans).
No relocation reimbursement provided.
This position description is not intended to be a complete listing of activities, duties or responsibilities that are required of the employee holding this position. Duties, responsibilities and activities may be changed or others may be assigned at any time by the Company with notice to the employee.
Aechelon Technology is an equal opportunity employer. We are committed to providing access and opportunities to individuals with disabilities. If you are an applicant who is unable to fully utilize/access our application process because of a disability, Aechelon Technology will provide a reasonable accommodation. Please send an email to hr_team@aechelon.com to request that accommodation, and please be sure to include a detailed description of your requested accommodation, your name and preferred method of contact.

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