ZipRecruiter

Log In

1

Freelance Machine Learning Data Annotation Jobs in Santa Clara, CA

Apple

Machine Learning - Data Scientist

Sunnyvale, CA

$150K - $277K/yr

  • Medical

  • Dental

  • Retirement

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 ...

YO AI Labs

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 ...

YO AI Labs

AI Data Science Expert - Remote

San Jose, 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 ...

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 ...

Apple

Data Scientist

Sunnyvale, CA

$184K - $324K/yr

  • Medical

  • Dental

  • Retirement

You will collaborate closely with algorithm engineers, machine learning researchers, QA, annotation ... Description As a Data Scientist focused on Algorithm Evaluation, you will serve as a technical ...

Apple

Data Scientist

Sunnyvale, CA · On-site

You will collaborate closely with algorithm engineers, machine learning researchers, QA, annotation ... Description As a Data Scientist focused on Algorithm Evaluation, you will serve as a technical ...

Apple, Inc.

Data Scientist

Sunnyvale, CA · On-site

You will collaborate closely with algorithm engineers, machine learning researchers, QA, annotation ... Description As a Data Scientist focused on Algorithm Evaluation, you will serve as a technical ...

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 ...

previous pagenext page

Showing results 21-40

All JobsMachine Learning Data Annotation JobsFreelance Machine Learning Data Annotation JobsFreelance Machine Learning Data Annotation Jobs in Santa Clara, CA

Freelance Machine Learning Data Annotation information

See Santa Clara, CA salary details

$15

$25

$41

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

As of Aug 18, 2026, the average hourly pay for freelance machine learning data annotation in Santa Clara, CA is $25.68, according to ZipRecruiter salary data. Most workers in this role earn between $20.34 and $29.38 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 Santa Clara, CA?

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

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

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

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

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

Freelance Machine Learning Data Annotation jobs near you

Machine Learning - Data Scientist

Apple

Sunnyvale, CA

$150K - $277K/yr

Full-time

Medical, Dental, Retirement

Re-posted 4 days ago

Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers

Job description

Do you have a passion for computer vision and solving deep learning problems? 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 play a critical part in crafting robust evaluation frameworks, using both traditional statistical methods and modern techniques like LLM-as-a-Judge! The ideal candidate combines strong analytical thinking, expertise in Python, and advanced knowledge of statistical methodologies and data quality standards.
This role involves collaboration with teams at Apple passionate about developing foundation models, including ML engineers, data scientists, and ML Infrastructure engineers to deliver amazing user experiences!
Description
Develop robust methodologies to assess the performance of foundation models (e.g., LLMs, vision-language models, etc.) across diverse tasks.
Leverage LLMs as judges to perform subjective and open-ended model evaluations (e.g., for summarization, reasoning, or multimodal generation tasks).
Build, curate, and lead evaluation datasets and benchmarks.
Advanced proficiency in at least one scripting language, preferably Python.
Collaborate with research, engineering, and product teams to define evaluation goals aligned with user experience and product quality.
Conduct failure analysis and uncover edge cases to improve model robustness.
Contribute to our tools and infrastructure to automate and scale evaluation processes.
Preferred Qualifications
Experience working with open-source evaluation tools like OpenEval, ELO-based ranking, or LLM-as-a-Judge frameworks.
Familiarity with prompt engineering, few-shot or zero-shot evaluation techniques.
Experience evaluating generative models (e.g., text generation, image generation).
Prior contributions to ML benchmarks or public evaluations.
Strong interpersonal skills.
Minimum Qualifications
BS and a minimum of 3 years relevant industry experience
Strong experience in evaluating supervised, unsupervised, and deep learning models.
Hands-on experience evaluating LLMs and using them as scoring/judging mechanisms.
Familiarity with multimodal models (e.g., image + text, video + audio) and related evaluation challenges.
Proficiency in Python and libraries such as NumPy, pandas, scikit-learn, PyTorch, or TensorFlow.
Solid understanding of statistical testing, sampling, confidence intervals, and metrics (e.g., precision/recall, BLEU, ROUGE, FID, etc.).
Strong documentation skills, including the ability to write technical reports and present to non-technical audiences.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $150,400 and $277,600, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apple logo

About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

View All Apple Jobs

Apply