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Freelance Machine Learning Data Annotation Jobs in California

Sunday Inc

Data Annotation Lead

Redwood City, CA · On-site

You'll work in coordination with Machine Learning, Software engineering, and Data to define the framework and tools on which to build a data annotation team around. Your role is vital to ensuring our ...

Welocalize, Inc.

Data Labeling Associate

San Diego, CA · On-site

$17 - $22/hr

Modify and refine machine learning data creation, annotation, and rating guidelines. Model Training and Evaluation: * Initiate model training processes using internal tools and command-line ...

Encord

Human Data Operations Strategist

San Francisco, CA · On-site

$130K - $210K/yr

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 ...

Encord

Human Data Operations Strategist

San Francisco, CA · On-site

$130K - $210K/yr

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 ...

Apple

Machine Learning Engineer

Cupertino, CA · On-site

$187K - $220K/yr

Develop data annotation tools with integrated machine learning models for efficient data annotation. 40 hours/week. At Apple, base pay is one part of our total compensation package and is determined ...

Apple

Machine Learning Engineer

Cupertino, CA · On-site +1

$187K - $220K/yr

Develop data annotation tools with integrated machine learning models for efficient data annotation. 40 hours/week. At Apple, base pay is one part of our total compensation package and is determined ...

Apple

Machine Learning Data Engineer

Cupertino, CA · On-site

$141K - $169K/yr

Description 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 ...

NTENT

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 ...

NTENT

Machine Learning Engineer

Carlsbad, CA

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 ...

Apple

Machine Learning Data Engineer

Cupertino, CA

$184K - $324K/yr

Description 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 ...

FieldAI

2.53 3D Machine Learning Engineer

Irvine, CA · On-site

... 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 ...

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Freelance Machine Learning Data Annotation information

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.
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:
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Freelance Machine Learning Data Annotation jobs near you
Data Scientist - Survey Design, Data Annotation, and Machine Learning Evaluation

Data Scientist - Survey Design, Data Annotation, and Machine Learning Evaluation

Apple

Cupertino, CA • On-site

Full-time

Re-posted 16 days ago

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 667 frontline employees who took The Breakroom Quiz

5th of 30 rated technology retailers

Job description

Apple is where individual imaginations gather together, committing to the values that lead to
great work. Every new product we build, service we create, or experience we deliver is the
result of us making each other's ideas stronger. The diversity of our people and their thinking
inspires the innovation that runs through everything we do. When we bring everybody in, we
can do the best work of our lives. Here, you'll do more than join something - you'll add
something.
Description
The Special Projects team at Apple is developing novel user-facing conversational features that
leverage the multimodal capabilities of state-of-the-art foundation models. As part of this
process, we generate real-world and simulated data, gather human data annotations, analyze
the results, and use them to build and evaluate Large Language Model judges. We are looking
for a skilled Data Scientist to join our Machine Learning Evaluations teams. This person will
work closely with ML Engineers to manage and analyze our human and automated data
annotation processes, and to develop, test, and refine LLM judges for generative AI model
evaluation. A successful candidate is experienced in survey design, data annotation, LLM
prompt engineering and prompt optimization, and has strong statistical analysis skills.
Minimum Qualifications
BA or Master's degree in Data Science, Statistics, or a quantitative social science field
2+ years of hands-on experience working in survey design and human data annotation
Proficiency in Python
Excellent communication skills
Preferred Qualifications
PhD in Data Science, Statistics, or a quantitative social science field
Hands-on industry experience with product-focused statistical analysis
Experience working with large-scale multimodal data and data-annotation pipelines
Experience with LLM prompt engineering & prompt optimization
Experience with LLM auto-judges for generative AI model evaluation
A track record of publications or technical presentations in Data Science or a related field
Excellent at cross-functional collaboration

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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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

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