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Freelance Machine Learning Data Annotation Jobs (NOW HIRING)

Collaborate closely with Machine Learning and Mapping engineers to provide feedback on labeling ... Preferred : • Prior experience in data annotation for autonomous driving, robotics, or computer ...

Expert Python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels) * Expert statistical analysis and machine learning - deep understanding of algorithms, methods, and their ...

Collaborate closely with Machine Learning and Mapping engineers to provide feedback on labeling ... Prior experience in data annotation for autonomous driving, robotics, or computer vision.

... AI) and machine learning (ML). Q Analysts is headquartered in San Jose, CA with a presence ... Q Analysts is looking for Data Annotation Technicians to support Ground Truth Data Collection ...

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 ...

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 ...

Collaborate closely with Machine Learning and Mapping engineers to provide feedback on labeling ... Prior experience in data annotation for autonomous driving, robotics, or computer vision.

Machine Learning Engineer

Manhattan, NY · Remote

$154K/yr

Prior experience with data annotation, data labeling, or AI evaluation workflows * Familiarity with ... Freelance autonomy with the substance of meaningful, high-impact technical work * Gain rare, hands ...

Senior Machine Learning Expert

Denver, CO · Remote

$89K - $110K/yr

Prior experience with data annotation, data quality assurance, or AI evaluation pipelines * Top ... Freelance autonomy with the substance of genuinely meaningful, high-impact work * Get rare, behind ...

... 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 ...

... experience in Machine Learning , Data Science , Software Engineering , Computer Science ... Prior experience with data annotation, labeling, evaluation, or human feedback collection.

Senior Machine Learning Expert

Manhattan, NY · Remote

$95K - $118K/yr

Prior experience with data annotation, data quality assurance, or AI evaluation systems * Top-tier ... Freelance autonomy with the structure of meaningful, high-impact technical work * Collaborate with ...

Machine Learning Data Engineer

Cupertino, CA · On-site

$141K - $169K/yr

We are seeking a highly experienced and strategic Machine Learning Data Engineer to drive our machine learning data with a strong focus on quality. In this role, you will transform ambiguous data ...

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Freelance Machine Learning Data Annotation information

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How much do freelance machine learning data annotation jobs pay per hour?

As of Jun 18, 2026, the average hourly pay for freelance machine learning data annotation in the United States is $21.87, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $25.00 per hour, depending on experience, location, and employer.

What is the difference between Freelance Machine Learning Data Annotation vs Data Labeler?

AspectFreelance Machine Learning Data AnnotationData Labeler
CredentialsBasic understanding of annotation tools, sometimes with specialized domain knowledgeTypically no formal credentials required
Work EnvironmentRemote, flexible, project-basedOften remote or in-house, depending on employer
Industry UsageUsed in AI/ML development for training datasetsUsed in data preparation for various industries, including AI
Search/Comparison IntentFocuses on freelance opportunities, project scope, and toolsMore 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 key skills and qualifications needed to thrive as a Freelance Machine Learning Data Annotation specialist, and why are they important?

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 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 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.
More about Freelance Machine Learning Data Annotation jobs
What cities are hiring for Freelance Machine Learning Data Annotation jobs? Cities with the most Freelance Machine Learning Data Annotation job openings:
What are the most commonly searched types of Machine Learning Data Annotation jobs? The most popular types of Machine Learning Data Annotation jobs are:
What states have the most Freelance Machine Learning Data Annotation jobs? States with the most job openings for Freelance Machine Learning Data Annotation jobs include:
Data Domain Architect Lead

Data Domain Architect Lead

JPMorgan Chase & Co.

Wilmington, DE • On-site

Full-time

Medical, Retirement

Posted 14 days ago


JPMorgan Chase & Co. rating

8.1

Company rating: 8.1 out of 10

Based on 470 frontline employees who took The Breakroom Quiz

46th of 141 rated banks


Job description

Job Description
Machine Learning and Artificial Intelligence play a critical role in transforming Consumer and Community Banking Operations. The ability to utilize data in meaningful ways allows us to develop solutions which both our customers and employees can benefit from. Customers expect tailored servicing and Chase is looking to deliver personalization to meet their needs. This is powered by high-quality annotated data and detailed annotation schemes that are the backbone of impactful Artificial Intelligence/Machine Learning ( AI/ML)L algorithms and applications.
As a Data Domain Architect Lead within the Data Annotation team , you will use your domain expertise and people-leading experience to partner your team closely with teams in Data Science, Analytics, and Engineering to develop machine learning solutions. This will involve the collection, curation, annotation, enrichment, and validation of data and the development of taxonomies and other linguistic resources to help train machine learning models, drive insight, analysis, and possible content creation.
Job responsibilities
  • Manage and coach a team of Machine Learning Data Domain analysts to support data annotation and label data/content using annotation tools and analysis
  • Partner with leads in Data Science, Engineering, and Analytics to develop strategies to optimize training data for machine learning models
  • Lead efforts to identify patterns and trends in conversational data through Natural Language Processing and/or other computational linguistic approaches
  • Collaborate with stakeholders on evaluating the quality of machine learning classification and other output
  • Actively contribute to the team's continuous learning mindset by bringing in new ideas and perspectives that stretch the thinking of the group

Required qualifications, capabilities, and skills
  • 6+ years of related experience in development of machine learning solutions
  • Familiar with industry annotation and labeling methods
  • Experience with various data modeling techniques and tools
  • Familiar with Finance and Banking products
  • Broad expertise in data technologies; i.e., data warehousing, data processing, data quality concepts, Business Intelligence tools and analytical tools, unstructured data, machine learning
  • Excellent analytical and problem-solving skills and the ability to pay close attention to detail
  • Experience using Python in working with and analyzing large real-world datasets
  • Working knowledge of information and data retrieval
  • Working knowledge of machine learning and artificial intelligence paradigms and libraries
  • Familiar with Large Language Models (LLMs) and prompt engineering

Preferred qualifications, capabilities, and skills
  • Masters or PhD in a related field, or Bachelors
  • Technical understanding of common relational database systems; i.e., Teradata and Oracle
  • Excellent command of the Structured Query Language (SQL)
  • Knowledge of SAS or Scala, and Python languages
  • Knowledge of Advanced Statistics
  • Advanced analytical thinking and problem-solving skills
  • Strong interpersonal & communication skills

About Us
Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
Equal Opportunity Employer/Disability/Veterans
About the Team
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.
The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

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