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Data Annotation Jobs in Phoenix, AZ (NOW HIRING)

TSMC

Senior Data Engineer / Data Curator

Phoenix, AZ · On-site

$105K - $143K/yr

... 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. • ...

General Motors

Senior AI/ML Engineer

Phoenix, AZ · On-site +1

$103K - $142K/yr

Apply ML to labeling itself Collaborate with ML engineers to design and integrate ML-driven data annotation (pre-labeling, autolabeling, active learning loops), helping us move from human-only to ...

TSMC

Senior Data Engineer / Data Curator

Phoenix, AZ

$130K - $177K/yr

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.

TSMC

Senior Data Engineer / Data Curator

Phoenix, AZ · On-site

$130K - $177K/yr

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.

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Data Annotation information

Is data annotation a legitimate?

Data annotation is a legitimate job that involves labeling data such as images, text, or audio to help train machine learning models. It is commonly performed remotely and requires attention to detail, basic technical skills, and familiarity with annotation tools. Many companies hire data annotators as part of their AI development teams.

What does a typical workday look like for someone in a Data Annotation role?

A typical workday as a Data Annotator involves reviewing datasets—such as images, audio, text, or video—and accurately labeling or categorizing information according to specific project guidelines. Most Data Annotators work independently, but they often collaborate with project managers or data scientists to clarify requirements and resolve ambiguities. Tasks may be repetitive, but adhering to precise standards is vital for maintaining data quality. Work environments can range from technology companies to remote or freelance settings, and advancement opportunities exist as team leads or quality assurance specialists for those who excel in consistency and reliability.

What is a Data Annotation job?

A Data Annotation job involves labeling and categorizing data, such as text, images, audio, or video, to help train machine learning models. Annotators apply tags, bounding boxes, or classifications to data based on specific guidelines. This process improves the accuracy of AI systems in recognizing patterns and making predictions. Many data annotation jobs require attention to detail and familiarity with specific domains. It is commonly used in applications like autonomous driving, natural language processing, and computer vision.

What are the key skills and qualifications needed to thrive in the Data Annotation position, and why are they important?

To thrive in Data Annotation, you need strong attention to detail, accuracy, and basic data handling skills, often supported by a high school diploma or equivalent. Familiarity with annotation platforms, data labeling software, or content management systems is frequently required, though specific certifications are rare. Excellent communication, time management, and the ability to focus on repetitive tasks distinguish top performers in this role. These skills are crucial because accurate and consistent data annotation directly impacts the quality of machine learning models and AI applications.

What does a data annotator do?

A data annotator labels and tags data such as images, text, or videos to help machine learning models understand and learn from the data. They use tools and follow guidelines to ensure accuracy and consistency, often working with large datasets in a structured environment. Attention to detail and knowledge of annotation tools are important for this role.

Do people actually make money on data annotation?

Data annotation jobs can provide a source of income, with pay rates varying based on the complexity of tasks, platform, and experience. Many annotators earn hourly or per-task wages, but earnings often depend on the volume of work completed and the employer's pay structure.

Is it hard to get hired for data annotation?

Getting hired for a data annotation role generally depends on the employer's requirements, such as attention to detail and basic computer skills. Many positions are entry-level and may not require prior experience or certifications, making them accessible to a wide range of applicants. However, competition can vary based on the number of available jobs and the quality of applicants.
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Data Annotation jobs near you
Infographic showing various Data Annotation job openings in Phoenix, AZ as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Senior Data Engineer / Data Curator

TSMC

Phoenix, AZ • On-site

$105K - $143K/yr

Full-time

Posted 28 days ago

TSMC rating

8.2

Company rating: 8.2 out of 10

Based on 19 frontline employees who took The Breakroom Quiz

37th of 139 rated electronics manufacturers

Job description

Job Summary:
TSMC Arizona is a leading semiconductor manufacturing company, offering an opportunity to work at the most advanced fab in the United States. As a Senior Data Engineer in the AI Data Curation track, you will design and maintain scalable data pipelines, ensuring that the data for AI models is high-quality and aligned with ethical 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.
Qualifications:
Required:
• Bachelor's degree in Computer Science, Data Science, or a related field.
• 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.).
• Candidates must be willing and able to work on-site at our Phoenix Arizona facility.
• Communication
• Computer proficiency
• Presentation skills
• Listening
• Teamwork
Preferred:
• Experience with vector databases and indexing for LLMs (e.g., FAISS, Pinecone).
Company:
Established in 1987, TSMC is the world's first dedicated semiconductor foundry. Founded in 1987, the company is headquartered in Hsinchu, TWN, with a team of 10001+ employees. The company is currently Late Stage.

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