Responsibilities : • Oversee data annotation projects, translating complex AI and machine learning requirements into clear workflows and instructions for data annotation teams • Ensure the ...
Responsibilities : • Oversee data annotation projects, translating complex AI and machine learning requirements into clear workflows and instructions for data annotation teams • Ensure the ...
... data workflows, including collection, preprocessing, annotation, versioning, and model integration. • Implement and refine training strategies for large-scale AI systems, including vision, video ...
... data workflows, including collection, preprocessing, annotation, versioning, and model integration. • Implement and refine training strategies for large-scale AI systems, including vision, video ...
Machine Learning Data Engineer
Santa Clara, CA · Remote
$100K/mo
Machine Learning Data Engineer - Remote Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United ...
Machine Learning Data Engineer
Santa Clara, CA · Remote
$100K/mo
Machine Learning Data Engineer - Remote Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United ...
Machine Learning Engineer
Carlsbad, CA · On-site
Coordinate data collection and annotation efforts. * Work with real-time data and content coming from various data sources. * Manage machine learning data pipelines. * Design tests for machine ...
Machine Learning Engineer
Carlsbad, CA · On-site
Coordinate data collection and annotation efforts. * Work with real-time data and content coming from various data sources. * Manage machine learning data pipelines. * Design tests for machine ...
Machine Learning Engineer
Carlsbad, CA · On-site
Coordinate data collection and annotation efforts. * Work with real-time data and content coming from various data sources. * Manage machine learning data pipelines. * Design tests for machine ...
Machine Learning Engineer
Carlsbad, CA · On-site
Coordinate data collection and annotation efforts. * Work with real-time data and content coming from various data sources. * Manage machine learning data pipelines. * Design tests for machine ...
Data Annotation Lead
San Francisco, CA · On-site
... and learning algorithms to power the robots of today and the physically-actuated devices of the ... The role We're looking for a Data Annotation Lead to own annotation operations and scale the team ...
Data Annotation Lead
San Francisco, CA · On-site
... and learning algorithms to power the robots of today and the physically-actuated devices of the ... The role We're looking for a Data Annotation Lead to own annotation operations and scale the team ...
Background in leading and managing complex programs that span across organizations and functions, with specific experience in Machine Learning data annotation or Human-in-the-Loop initiatives.
Background in leading and managing complex programs that span across organizations and functions, with specific experience in Machine Learning data annotation or Human-in-the-Loop initiatives.
... performance of machine learning models through precise data analysis and quality assurance ... Conduct detailed data annotation and quality assurance of natural language datasets following ...
... performance of machine learning models through precise data analysis and quality assurance ... Conduct detailed data annotation and quality assurance of natural language datasets following ...
... annotation, which is crucial for their autonomous construction robots. This role involves working at the intersection of applied machine learning, data infrastructure, and robotics to enhance the ...
... annotation, which is crucial for their autonomous construction robots. This role involves working at the intersection of applied machine learning, data infrastructure, and robotics to enhance the ...
You have: * 4-5+ years of experience in data analysis, operations, or program management with a focus on machine learning data annotation, taxonomy design, or human-in-the-loop workflows.
You have: * 4-5+ years of experience in data analysis, operations, or program management with a focus on machine learning data annotation, taxonomy design, or human-in-the-loop workflows.
Machine Learning / Data Scientist
Bodega Bay, CA · On-site
$110K - $140K/yr
Job Summary Our client is looking for a machine learning engineer to join our existing ML team in developing and refining a predictive application. The ideal candidate is adept at using large data ...
Quick apply
Machine Learning / Data Scientist
Bodega Bay, CA · On-site
$110K - $140K/yr
Job Summary Our client is looking for a machine learning engineer to join our existing ML team in developing and refining a predictive application. The ideal candidate is adept at using large data ...
... data annotation strategies and ensure high model performance and generalization. Qualifications : Required : • Bachelor's or Master's degree in Computer Science, Machine Learning, Robotics, or a ...
... data annotation strategies and ensure high model performance and generalization. Qualifications : Required : • Bachelor's or Master's degree in Computer Science, Machine Learning, Robotics, or a ...
PROLIM Global Corporation (www.prolim.com) is currently seeking Machine Learning Data Collection Specialist for location Burlingame, California, United States for one of our Top clients . * 3 + year ...
Quick apply
PROLIM Global Corporation (www.prolim.com) is currently seeking Machine Learning Data Collection Specialist for location Burlingame, California, United States for one of our Top clients . * 3 + year ...
The Video Engineering Data Analytics and Quality group is seeking an expert in evaluating machine learning and deep learning models, including foundation models and multimodal systems. This role will ...
The Video Engineering Data Analytics and Quality group is seeking an expert in evaluating machine learning and deep learning models, including foundation models and multimodal systems. This role will ...
The Video Engineering Data Analytics and Quality group is seeking an expert in evaluating machine learning and deep learning models, including foundation models and multimodal systems. This role will ...
The Video Engineering Data Analytics and Quality group is seeking an expert in evaluating machine learning and deep learning models, including foundation models and multimodal systems. This role will ...
Machine Learning - Data Scientist
$150K - $277K/yr
The Video Engineering Data Analytics and Quality group is seeking an expert in evaluating machine learning and deep learning models, including foundation models and multimodal systems. This role will ...
Machine Learning - Data Scientist
$150K - $277K/yr
The Video Engineering Data Analytics and Quality group is seeking an expert in evaluating machine learning and deep learning models, including foundation models and multimodal systems. This role will ...
Technical Program Manager, Data Engine
Redwood City, CA · On-site
$157K - $204K/yr
They are seeking a Technical Program Manager, Data Engine to manage data annotation and collection projects, ensuring high-quality data delivery for machine learning experiments. Responsibilities ...
Technical Program Manager, Data Engine
Redwood City, CA · On-site
$157K - $204K/yr
They are seeking a Technical Program Manager, Data Engine to manage data annotation and collection projects, ensuring high-quality data delivery for machine learning experiments. Responsibilities ...
Data Annotation Analyst
San Francisco, CA · On-site
$71K - $89K/yr
Perform quality control and labeling for images used for machine learning (ML) models * Manage a ... Upload prioritized image data for labeling * Create and track metrics for labelers * Iterate on ...
Data Annotation Analyst
San Francisco, CA · On-site
$71K - $89K/yr
Perform quality control and labeling for images used for machine learning (ML) models * Manage a ... Upload prioritized image data for labeling * Create and track metrics for labelers * Iterate on ...
Software Engineer (C++/Java) - Data Platform
Sunnyvale, CA · On-site
$136K - $163K/yr
Contribute to large-scale machine learning and data platforms , including feature extraction, data annotation, and model operationalization. * Develop full-stack applications supporting big-data ...
Software Engineer (C++/Java) - Data Platform
Sunnyvale, CA · On-site
$136K - $163K/yr
Contribute to large-scale machine learning and data platforms , including feature extraction, data annotation, and model operationalization. * Develop full-stack applications supporting big-data ...
AI Data Scientist Expert - Remote
Palo Alto, CA · Remote
$100 - $200/hr
... Annotation * Data Interpretation * Fact Checking * Independent Research * Problem-Solving * Attention to Detail Preferred Qualifications * 3+ years of experience in Data Science, Machine Learning ...
Quick apply
AI Data Scientist Expert - Remote
Palo Alto, CA · Remote
$100 - $200/hr
... Annotation * Data Interpretation * Fact Checking * Independent Research * Problem-Solving * Attention to Detail Preferred Qualifications * 3+ years of experience in Data Science, Machine Learning ...
Freelance Machine Learning Data Annotation information
What is freelance machine learning data annotation?
Freelance machine learning data annotation involves labeling or tagging data—such as images, text, audio, or video—to help train machine learning models. As a freelancer, you work independently or through platforms, completing specific annotation tasks assigned by companies or researchers. This work is essential because high-quality labeled data is required for AI systems to learn and make accurate predictions. Annotators may categorize images, transcribe speech, or highlight relevant information in documents. The flexibility of freelancing allows you to choose projects and work remotely.
What are the key skills and qualifications needed to thrive as a freelance machine learning data annotation specialist?
To thrive as a Freelance Machine Learning Data Annotation specialist, you need attention to detail, basic knowledge of data labeling concepts, and familiarity with machine learning data types. Experience with annotation tools (such as Labelbox, RectLabel, or CVAT) and understanding of data privacy protocols are commonly required. Strong communication, time management, and the ability to follow complex guidelines are essential soft skills for delivering accurate results. These skills ensure high-quality, consistent data annotation, which is critical for effective machine learning model training and performance.
What are some common challenges faced by freelance machine learning data annotators, and how can they be managed?
Freelance machine learning data annotators often encounter challenges such as maintaining data accuracy, handling repetitive tasks, and understanding complex annotation guidelines. Staying organized and regularly reviewing project instructions can help ensure consistency and quality in annotations. Additionally, communicating proactively with project managers and utilizing annotation tools efficiently can help manage workload and clarify uncertainties. Building expertise in different data types (text, image, audio) also allows annotators to diversify their projects and reduce monotony.
What is the difference between Freelance Machine Learning Data Annotation vs Data Labeler?
| Aspect | Freelance Machine Learning Data Annotation | Data Labeler |
|---|---|---|
| Credentials | Basic understanding of annotation tools, sometimes with specialized domain knowledge | Typically no formal credentials required |
| Work Environment | Remote, flexible, project-based | Often remote or in-house, depending on employer |
| Industry Usage | Used in AI/ML development for training datasets | Used in data preparation for various industries, including AI |
| Search/Comparison Intent | Focuses on freelance opportunities, project scope, and tools | More general, often employed by companies for data labeling tasks |
Freelance Machine Learning Data Annotation involves independently completing annotation tasks for AI models, often with specialized tools and domain knowledge. Data Labelers typically perform similar tasks but may work as employees or contractors within a company. The main difference lies in the freelance nature and project-based work of data annotation roles.
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 Freelance Machine Learning Data Annotation jobs in California?
For Freelance Machine Learning Data Annotation jobs in California, the most frequently searched job titles are:
What job categories do people searching Freelance Machine Learning Data Annotation jobs in California look for?
The top searched job categories for Freelance Machine Learning Data Annotation jobs in California are:
What cities in California are hiring for Freelance Machine Learning Data Annotation jobs?
Cities in California with the most Freelance Machine Learning Data Annotation job openings:
Full-time
Re-posted 27 days ago
Job description
Job Summary:
Encord is a leading company in AI data management, supporting over 300 AI teams in optimizing their data workflows. The Human Data Operations Strategist will manage data annotation projects, ensuring high-quality data is available for AI models while collaborating with various teams and clients to refine processes and implement effective workflows.
Responsibilities:
• 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 quality by designing and refining annotation processes, auditing results, and implementing feedback loops
• Act as a trusted advisor to clients, helping them design and implement the best data annotation workflow for their human annotation process
• Provide guidance and feedback to the annotation team, ensuring team members are equipped with the context and skills needed to perform high-quality work aligned with project requirements and best practices
• Work closely with product and engineering teams to drive improvements in AI training data processes, tools, and methodologies
Qualifications:
Required:
• 3–7 years of professional experience, with a strong preference for backgrounds in top-tier strategy consulting and/or operations or data roles at leading AI or technology companies
• Proven ability to own complex, multi-stakeholder workflows end-to-end — from scoping and planning through execution, quality assurance, and iteration
• Working proficiency in Python or SQL, with the ability to query data, automate workflows, or audit annotation outputs; broader familiarity with relational databases or data annotation tooling equally valued
• Experience designing or optimising data operations processes with a strong eye for quality, consistency, and scalability — ideally in a context involving human-in-the-loop workflows or structured labelling tasks
• Demonstrated ability to engage effectively with both technical stakeholders (ML engineers, data scientists) and non-technical clients, translating requirements clearly in both directions
• A sharp, execution-oriented operator with a consulting or AI company pedigree — you bring structured thinking, strong project management instincts, and a bias for getting things done
• Analytically rigorous and comfortable with ambiguity — you break down complex operational challenges from first principles and build clear, actionable plans to solve them
• Technically fluent enough to get hands-on with data — whether that's querying a database, auditing annotation outputs, or automating a workflow in Python
• Passionate about AI and machine learning, with genuine curiosity about how data quality and operations underpin model performance
• A natural communicator who can translate fluidly between ML engineers and non-technical clients, keeping complex multi-stakeholder projects on track
• Entrepreneurial and collaborative — you thrive in fast-paced environments and take ownership without waiting to be told what to do
Preferred:
• Bonus: hands-on experience with computer vision, generative AI, or multimodal data workflows; prior exposure to data annotation platforms or quality management frameworks; experience coaching or managing operational teams
Company:
Encord is the AI native data Infrastructure company. We help teams curate, manage, and annotate the data needed to train and run AI Founded in 2021, the company is headquartered in San Francisco, USA, with a team of 201-500 employees. The company is currently Growth Stage.
Encord is a leading company in AI data management, supporting over 300 AI teams in optimizing their data workflows. The Human Data Operations Strategist will manage data annotation projects, ensuring high-quality data is available for AI models while collaborating with various teams and clients to refine processes and implement effective workflows.
Responsibilities:
• 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 quality by designing and refining annotation processes, auditing results, and implementing feedback loops
• Act as a trusted advisor to clients, helping them design and implement the best data annotation workflow for their human annotation process
• Provide guidance and feedback to the annotation team, ensuring team members are equipped with the context and skills needed to perform high-quality work aligned with project requirements and best practices
• Work closely with product and engineering teams to drive improvements in AI training data processes, tools, and methodologies
Qualifications:
Required:
• 3–7 years of professional experience, with a strong preference for backgrounds in top-tier strategy consulting and/or operations or data roles at leading AI or technology companies
• Proven ability to own complex, multi-stakeholder workflows end-to-end — from scoping and planning through execution, quality assurance, and iteration
• Working proficiency in Python or SQL, with the ability to query data, automate workflows, or audit annotation outputs; broader familiarity with relational databases or data annotation tooling equally valued
• Experience designing or optimising data operations processes with a strong eye for quality, consistency, and scalability — ideally in a context involving human-in-the-loop workflows or structured labelling tasks
• Demonstrated ability to engage effectively with both technical stakeholders (ML engineers, data scientists) and non-technical clients, translating requirements clearly in both directions
• A sharp, execution-oriented operator with a consulting or AI company pedigree — you bring structured thinking, strong project management instincts, and a bias for getting things done
• Analytically rigorous and comfortable with ambiguity — you break down complex operational challenges from first principles and build clear, actionable plans to solve them
• Technically fluent enough to get hands-on with data — whether that's querying a database, auditing annotation outputs, or automating a workflow in Python
• Passionate about AI and machine learning, with genuine curiosity about how data quality and operations underpin model performance
• A natural communicator who can translate fluidly between ML engineers and non-technical clients, keeping complex multi-stakeholder projects on track
• Entrepreneurial and collaborative — you thrive in fast-paced environments and take ownership without waiting to be told what to do
Preferred:
• Bonus: hands-on experience with computer vision, generative AI, or multimodal data workflows; prior exposure to data annotation platforms or quality management frameworks; experience coaching or managing operational teams
Company:
Encord is the AI native data Infrastructure company. We help teams curate, manage, and annotate the data needed to train and run AI Founded in 2021, the company is headquartered in San Francisco, USA, with a team of 201-500 employees. The company is currently Growth Stage.