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Freelance Machine Learning Data Annotation Jobs in Moreno Valley, CA

VSolvit

DATA SCIENTIST II

Norco, CA · On-site

$115K - $130K/yr

In this role, you will apply advanced data analytics and machine learning techniques to explore large, complex datasets for unknown trends and patterns regarding customer behavior, product ...

Autodesk

Data Scientist, FP&A Solutions

Ontario, CA · On-site +1

Improve financial forecasting through statistical modeling, machine learning, driver-based forecasting, and scenario analysis * Automate recurring FP&A processes, including data preparation, variance ...

Socket.dev

Data Engineering Scientist

Ontario, CA · On-site

$100 - $125/hr

Our team delivers extensive engineering and industrial AI expertise along with cutting-edge digitalization solutions with a focus on industrial data, AI, machine learning, industrial edge, IIoT ...

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All JobsMachine Learning Data Annotation JobsFreelance Machine Learning Data Annotation JobsFreelance Machine Learning Data Annotation Jobs in Moreno Valley, CA

Freelance Machine Learning Data Annotation information

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

As of Sep 7, 2026, the average hourly pay for freelance machine learning data annotation in Moreno Valley, CA is $22.89, according to ZipRecruiter salary data. Most workers in this role earn between $18.12 and $26.15 per hour, depending on experience, location, and employer.

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?

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.

Can I work for freelance machine learning data annotation with no experience?

Freelance machine learning data annotation jobs often do not require prior experience, as many tasks involve simple labeling or categorization that can be learned quickly. Basic computer skills, attention to detail, and familiarity with annotation tools are helpful, and training is usually provided. However, building a portfolio or gaining some familiarity with data annotation platforms can improve job prospects.

What are popular job titles related to Freelance Machine Learning Data Annotation jobs in Moreno Valley, CA?

For Freelance Machine Learning Data Annotation jobs in Moreno Valley, CA, the most frequently searched job titles are:

What job categories do people searching Freelance Machine Learning Data Annotation jobs in Moreno Valley, CA look for?

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Cities near Moreno Valley, CA with the most Freelance Machine Learning Data Annotation job openings:

Freelance Machine Learning Data Annotation jobs near you

Biology Research Scientist (Remote | $60-$100/hr)

Synthires

Riverside, CA • On-site

$60 - $100/hr

Other

Posted 12 days ago

Job description

Molecular Biologist


Position: Molecular Biologist


Type: Contract


Compensation: $60–$9100/hour


Location: Remote


About the Opportunity :


This opportunity is for experienced Molecular Biologists with expertise in molecular biology, genetics, gene editing, DNA/RNA analysis, and laboratory research to contribute to advanced AI research and evaluation projects. You'll apply your scientific expertise to evaluate expert-level biological content, assess AI-generated outputs, and help improve the accuracy, reasoning, and performance of next-generation AI systems.

No prior AI experience is required. Your molecular biology expertise and research experience are the primary qualifications for success in this role. Professionals with hands-on experience in CRISPR, PCR, cloning, sequencing, genomics, and molecular diagnostics are especially encouraged to apply.


Responsibilities

  • Conduct and evaluate molecular biology research involving DNA, RNA, proteins, and gene expression.
  • Review and assess AI-generated scientific content for technical accuracy, completeness, and scientific reasoning.
  • Apply expertise in PCR, qPCR, cloning, sequencing, CRISPR gene editing, genotyping, and molecular assays.
  • Analyze DNA/RNA sequences, molecular pathways, genetic variation, and cellular mechanisms.
  • Design, interpret, and evaluate molecular biology experiments and laboratory workflows.
  • Translate complex molecular biology concepts into clear, structured documentation for AI training and evaluation.
  • Collaborate with interdisciplinary teams to ensure scientific accuracy, consistency, and data quality.
  • Apply structured evaluation frameworks and scientific judgment to improve AI model performance.


Required Qualifications

  • Bachelor's degree or higher in Molecular Biology, Genetics, Biotechnology, Cell Biology, Biochemistry, or a related Life Sciences discipline.
  • Strong hands-on experience with molecular biology techniques, PCR, DNA/RNA extraction, cloning, sequencing, and gene expression analysis.
  • Experience working in laboratory or wet lab research environments.
  • Excellent scientific reasoning, analytical thinking, and problem-solving skills.
  • Strong written and verbal communication skills with exceptional attention to scientific detail.
  • Ability to work independently in a fully remote environment.


Preferred Qualifications

  • Master's degree or PhD in Molecular Biology, Genetics, Biotechnology, Biochemistry, or a related field.
  • Experience with CRISPR, genomics, transcriptomics, bioinformatics, synthetic biology, or molecular diagnostics.
  • Familiarity with AI, machine learning, scientific data annotation, or AI model evaluation.
  • Experience developing scientific evaluation frameworks, quality assurance processes, or research review standards.
  • Experience collaborating with cross-functional or remote research teams.


Compensation

  • Competitive compensation of $60–$100/hour.
  • Weekly payments.
  • Independent contractor engagement.


Application Process

  1. Easy Apply on LinkedIn
  2. Check Email for Next Steps
  3. Participate in Resume Evaluation & Interview Stage


Apply