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Freelance Machine Learning Data Annotation Jobs in Phoenix, AZ

Senior Data Engineer / Data Curator

Phoenix, AZ · On-site

$130K - $177K/yr

... in machine learning or AI-driven environments. * Strong proficiency in Python (Pandas, NumPy) and ... Experience with data annotation tools and platforms for manual or semi-automated labeling.

... in machine learning or AI-driven environments. * Strong proficiency in Python (Pandas, NumPy) and ... Experience with data annotation tools and platforms for manual or semi-automated labeling.

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

Azure Machine Learning * Data Lakes & Data Warehousing * Data Governance, Metadata Management, and Data Lineage Key Responsibilities * Analyze, profile, and validate data across legacy and target ...

Data Engineer : F2F @ Phoenix, AZ

Phoenix, AZ · On-site

$113K - $136K/yr

Company Description NucleusTeq is a global leader in software services, specializing in Generative AI, Machine Learning, Data Modernization, Cloud Computing, and Enterprise Automation. Headquartered ...

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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 Aug 19, 2026, the average hourly pay for freelance machine learning data annotation in Phoenix, AZ is $21.71, according to ZipRecruiter salary data. Most workers in this role earn between $17.16 and $24.81 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 Phoenix, AZ?

The most popular types of Machine Learning Data Annotation jobs in Phoenix, AZ are:

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

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

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

What cities near Phoenix, AZ are hiring for Freelance Machine Learning Data Annotation jobs?

Cities near Phoenix, AZ with the most Freelance Machine Learning Data Annotation job openings:

Infographic showing various Freelance Machine Learning Data Annotation job openings in Phoenix, AZ as of July 2026, with employment types broken down into 19% Full Time, 7% Part Time, 68% Contract, and 6% Nights. Highlights an 22% Physical, and 78% Remote job distribution, with an average salary of $45,160 per year, or $21.7 per hour.

Senior Data Engineer / Data Curator

TSMC

Phoenix, AZ • On-site

$130K - $177K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 3 days ago


TSMC rating

8.0

Company rating: 8.0 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

59th of 159 rated electronics manufacturers


Job description

Senior Data Engineer / Data Curator
A job at TSMC Arizona offers an opportunity to work at the most advanced semiconductor fab in the United States. TSMC Arizona's first fab will operate it's leading-edge semiconductor process technology (N4 process), starting production in the first half of 2025. The second fab will utilize its leading edge N3 and N2 process technology and be operational in 2028. The recently announced third fab will manufacture chips using 2nm or even more advanced process technology, with production starting by the end of the decade. America's leading technology companies are ready to rely on TSMC Arizona for the next generations of chips that will power the digital future.
As a Senior Data Engineer in the AI Data Curation track, you will ensure that the data powering our AI models is high-quality, well-organized, and fit for use in model training and deployment. You will play a key role in designing and maintaining scalable data pipelines, ensuring that data is clean, relevant, and aligned with ethical and compliance standards.
Responsibilities:
  • Design and implement data pipelines for processing, cleaning, and curating large datasets used in model training and fine-tuning.
  • Automate data cleaning processes (e.g., removing noise, duplicates, irrelevant content) and ensure datasets are appropriately labeled and structured.
  • Collaborate with model teams to ensure data aligns with model requirements and performance goals.
  • Assess and mitigate bias in datasets, ensuring that models are trained on diverse and representative data.
  • Manage data storage and retrieval strategies, ensuring scalability and data consistency across different environments.
  • Conduct regular audits to ensure data integrity, privacy, and security compliance.

Minimum Qualifications/Requirements:
Education: Minimum degree required: Bachelor's degree in Computer Science, Data Science, or a related field.
Technical Skills:
  • 5+ years of experience in data engineering, data wrangling, or data curation, particularly in machine learning or AI-driven environments.
  • Strong proficiency in Python (Pandas, NumPy) and SQL for data manipulation and querying.
  • Familiarity with cloud-based data storage (AWS S3, Google Cloud Storage, etc.) and distributed systems for managing large datasets.
  • Experience with data annotation tools and platforms for manual or semi-automated labeling.
  • Experience with NLP data formats, such as JSONL, text, or embeddings, and an understanding of tokenization.
  • Experience managing data pipelines with tools like Apache Kafka, Apache Airflow, or similar ETL tools.
  • Strong knowledge of AI ethics, data privacy, and compliance standards (GDPR, CCPA, etc.).
  • Bonus: Experience with vector databases and indexing for LLMs (e.g., FAISS, Pinecone).

Interpersonal Skills:
  • Communication
  • Computer proficiency
  • Presentation skills
  • Listening
  • Teamwork

Candidates must be willing and able to work on-site at our Phoenix Arizona facility.
As a valued member of the TSMC family, we place a significant focus on your health and well-being. When you are at your best-physically, mentally, and financially-our company is at its best. We offer a comprehensive and competitive benefits program that provides the resources you need to help you manage your health and achieve your goals across many areas of your life. This includes a variety of medical, dental and vision plan offerings you can choose from that best fit your and your family's needs. Additionally, TSMC provides income-protection programs to financially assist you should you experience an injury or illness, and a 401(k)-retirement savings plan to help you secure your financial future. TSMC also offers competitive paid time-off programs and paid holidays allowing you to recharge and spend time with your family and loved ones.
Work Location: 5088 W. Innovation Circle, Phoenix, AZ 85083
TSMC is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected characteristic. We encourage all qualified individuals to apply, and we welcome applications from individuals with diverse backgrounds and experiences. Candidates must be able to perform the essential functions of the job with or without a reasonable accommodation. If you need a reasonable accommodation as part of this application process, please contact P_LOA@tsmc.com.
#LI-Onsite
Date: Jul 29, 2026
Country/Region: US
City: Phoenix
Company: TSMC Arizona

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