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Freelance Machine Learning Data Annotation Jobs in Sunnyvale, CA

YO AI Labs

AI Data Science 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 ...

Abaka AI

Machine Learning Engineer

Mountain View, CA · On-site

$175K - $275K/yr

... data collection and annotation services. Whether teams need raw data, curated datasets, or full ... About the Role We're hiring our first Machine Learning Engineer in the United States, a ...

Abaka AI

Machine Learning Engineer

Mountain View, CA

$175K - $275K/yr

... data collection and annotation services. Whether teams need raw data, curated datasets, or full ... About the Role We're hiring our first Machine Learning Engineer in the United States, a ...

Human Archive

Machine Learning Engineer

San Francisco, CA · On-site

$125 - $150/hr

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 ...

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 ...

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All JobsMachine Learning Data Annotation JobsFreelance Machine Learning Data Annotation JobsFreelance Machine Learning Data Annotation Jobs in Sunnyvale, CA

Freelance Machine Learning Data Annotation information

See Sunnyvale, CA salary details

$15

$25

$41

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

As of Sep 8, 2026, the average hourly pay for freelance machine learning data annotation in Sunnyvale, CA is $25.66, according to ZipRecruiter salary data. Most workers in this role earn between $20.34 and $29.33 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 the most commonly searched types of Machine Learning Data Annotation jobs in Sunnyvale, CA?

The most popular types of Machine Learning Data Annotation jobs in Sunnyvale, CA are:

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

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

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

The top searched job categories for Freelance Machine Learning Data Annotation jobs in Sunnyvale, CA are:

What cities near Sunnyvale, CA are hiring for Freelance Machine Learning Data Annotation jobs?

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

Freelance Machine Learning Data Annotation jobs near you
Infographic showing various Freelance Machine Learning Data Annotation job openings in Sunnyvale, CA as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $53,381 per year, or $25.7 per hour.

Machine Learning Data Scientists

Jobs for Humanity

San Francisco, CA

$174K - $193K/yr

Full-time

Re-posted 25 days ago

Key responsibilities

  • Collaborate with ML teams to design algorithms and identify opportunities to improve ranking and personalization.

  • Design and analyze large-scale experiments on grocery users to discover insights that enhance discovery platforms.

  • Present findings to senior management to inform business decisions.

Job description

Company Description
Jobs for Humanity is collaborating with Upwardly Global and with Uber to build an inclusive and just employment ecosystem. We support individuals coming from all walks of life.
Company Name: Uber
Job Description

About the Team Across thousands of storefronts each with thousands of products, Uber Grocery needs to decide exactly what products to show you, how to price them, and how to balance the tricky tradeoffs that come with delivery logistics. We build systems that deeply understand our products, users, and merchants to optimize the marketplace for all parties. Grocery & Retail is one of Uber's biggest new bets. Since launching in 2020, we've achieved an annual run rate of $7 billion in global gross bookings and integrated two strategic acquisitions, Cornershop and Drizly. Our team builds across the end-to-end grocery experience, including consumer growth, fulfillment flows, and catalog management.
What you will do
- Work closely with ML teams to design algorithms and uncover opportunities to improve ranking and personalization.
- Design and analyze large-scale experiments on grocery users in the Eats app to discover insights that improve our discovery platforms.
- Collaborate with Product, Engineering, Design, and other cross-functional partners to understand user behaviors to inform future product strategies.
- Present findings to senior management to inform business decisions.
Basic Qualifications
- 5+ years of industry experience working in personalization or search
- Experience in algorithm prototyping and development.
- Experience working with funnel optimization, user segmentation, cohort analysis, and lifetime value forecasting.
- Ability to use Python/PySpark for exploratory data analysis and modeling.
- Strong communication skills across technical, non-technical, and executive audiences.
Preferred Qualifications
- Ph.D., M.S., or Bachelor's degree in Statistics, Economics, Operations Research, or other quantitative fields.
- Experience in a technical leadership role.
- Experience in modern deep learning architectures and probabilistic models.
- Experience in modern generative AI, such as transformer architectures, diffusion models and prompting.
- Experience guiding and mentoring other Scientists.
- Excellent communication skills across technical, non-technical, and executive audiences.
For New York, NY-based roles:
The base salary range for this role is USD$174,000 per year - USD$193,500 per year.
For San Francisco, CA-based roles:
The base salary range for this role is USD$174,000 per year - USD$193,500 per year.
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link:
https://www.uber.com/careers/benefits
Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form. Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.

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