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Full Time Machine Learning Data Annotation Jobs in Phoenix, AZ

Champions Funding LLC

Data Scientist

Gilbert, AZ · On-site

Design, develop, and evaluate machine learning, statistical, and predictive models to solve complex ... Evaluate data quality, model performance, and AI system limitations while ensuring responsible ...

MY DR NOW

AI & Machine Learning Engineer

Chandler, AZ · On-site

$100K - $110K/yr

... LLMs), Machine Learning, and Generative AI * Build intelligent agents, RAG solutions, prompt ... Write advanced SQL queries to transform healthcare data into actionable intelligence * Collaborate ...

Intel

Sr. Machine Learning Engineer

Phoenix, AZ

$103K - $142K/yr

Machine Learning Engineer / Data Scientist** to join our team, working on agent harness research and model fine tuning. This role sits at the intersection of research and engineering: the ideal ...

Shamrock

Data Science Analyst

Phoenix, AZ · On-site

The Data Science Analyst is responsible for using data science, machine learning, statistical modeling, and advanced analytics to solve complex business problems across Supply Chain and Operations.

Axon

Senior Machine Learning Scientist

Scottsdale, AZ

$92K - $125K/yr

... data. What You'll Do Location: any cities with Axon Engineering Hub in US, Vietnam, EU (see * US ... in computer vision, machine learning, and deep learning, MLLMs, GenAI and integrate relevant ...

Axon

Senior Machine Learning Scientist

Scottsdale, AZ · On-site

$92K - $125K/yr

... data. What You'll Do Location: any cities with Axon Engineering Hub in US, Vietnam, EU (see * US ... in computer vision, machine learning, and deep learning, MLLMs, GenAI and integrate relevant ...

Encora

Solution Architect

Scottsdale, AZ

$190K - $191K/yr

... end machine learning pipelines, including data collection, preprocessing, annotation, model ... Full-time employment. CONTACT: Attn: HR Encora Innovations, LLC Saranya.Ezhilrajan@encora.com Must ...

Encora

Solution Architect

Scottsdale, AZ · On-site

$190K - $191K/yr

... end machine learning pipelines, including data collection, preprocessing, annotation, model ... Full-time employment. CONTACT: Attn: HR Encora Innovations, LLC Saranya.Ezhilrajan@encora.com Must ...

Connexzia

Data Analyst

Scottsdale, AZ

We are seeking a detail-oriented Data Analyst to join our team. In this role, you will be ... Experience with machine learning, predictive analytics, or AI-driven analytics. * Familiarity with ...

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Showing results 21-40

All JobsMachine Learning Data Annotation JobsFull Time Machine Learning Data Annotation JobsFull Time Machine Learning Data Annotation Jobs in Phoenix, AZ

Full Time Machine Learning Data Annotation information

See Phoenix, AZ salary details

$37.2K

$121.9K

$195.1K

How much do full time machine learning data annotation jobs pay per year?

As of Aug 16, 2026, the average yearly pay for full time machine learning data annotation in Phoenix, AZ is $121,868.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,800.00 and $135,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a full time machine learning data annotation specialist, and why are they important?

To thrive as a Full Time Machine Learning Data Annotation Specialist, you need strong attention to detail, basic data literacy, and familiarity with data labeling concepts, often supported by a high school diploma or equivalent. Proficiency in specialized annotation platforms, spreadsheet tools, and sometimes knowledge of Python or labeling frameworks is typically required. Reliability, patience, and effective communication are valuable soft skills for ensuring accuracy and collaborating with team members. These skills and qualities are crucial because they directly impact the quality of training data, which is essential for developing effective machine learning models.

What is a full time machine learning data annotation job?

Full time machine learning data annotation jobs involve labeling, tagging, or categorizing data such as images, text, audio, or video to help train machine learning models. Data annotators play a crucial role in ensuring that AI systems learn from high-quality, accurately labeled datasets. These positions often require attention to detail, consistency, and sometimes familiarity with the subject matter or specialized tools. Full-time roles may be remote or onsite and can span industries like autonomous vehicles, healthcare, retail, and more.

What are some common challenges faced by machine learning data annotators, and how are these typically addressed within a team?

Machine learning data annotators often encounter challenges such as maintaining consistency in labeling, handling ambiguous data, and meeting tight deadlines for large datasets. Teams usually address these by establishing clear annotation guidelines, conducting regular training sessions, and implementing quality assurance processes like peer reviews and spot checks. Collaboration with data scientists and project managers is also common, ensuring that annotators can ask questions and clarify uncertainties, leading to higher-quality labeled data and a supportive work environment.

What is the difference between Full Time Machine Learning Data Annotation vs Data Labeling Specialist?

AspectFull Time Machine Learning Data AnnotationData Labeling Specialist
CredentialsHigh school diploma or equivalent; some roles prefer technical certificationsHigh school diploma or equivalent; training often provided on the job
Work EnvironmentOffice or remote; collaborative with data science teamsRemote or office; focused on labeling tasks
Industry UsageUsed across AI/ML companies, tech firms, and startupsCommon in AI/ML, data services, and outsourcing companies
Job FocusCreating labeled datasets for machine learning modelsAnnotating data such as images, videos, or text for AI training

Full Time Machine Learning Data Annotation involves creating high-quality labeled datasets for AI models, often requiring technical understanding. Data Labeling Specialists focus on annotating data accurately, typically with less emphasis on technical skills. Both roles are essential in AI development but differ mainly in scope and technical complexity.

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:

What are popular job titles related to Full Time Machine Learning Data Annotation jobs in Phoenix, AZ?

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

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

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

Full Time Machine Learning Data Annotation jobs near you

Senior Data Engineer / Data Curator

Taiwan Semiconductor Manufacturing Company Limited

Phoenix, AZ • On-site

$130K - $177K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 19 days ago

Job description

Company
TSMC Arizona Corporation
Location
USA-Arizona
Posted
Apr 03, 2026
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
TSMC Core Values
At TSMC, we invite talented individuals who share our vision and values to contribute to our continued success. Our core values are the foundation of our culture, guiding every decision and action. We seek applicants who deeply resonate with these principles and embody them in their work:
  • Integrity: Tell the truth. We do not brag. We do not make commitments lightly. Once we make a commitment, we devote ourselves completely to meeting that commitment.
  • Commitment: Employees are dedicated to the company, view the company's success as their own and work diligently to make their best contributions. As commitment is mutual, the Company strives to serve the best interests of its employees.
  • Innovation: Innovation is the wellspring of the Company's growth. It means more than new ideas; it means putting ideas into practice.
  • Customer Trust: We strive to build deep and enduring relationships with our customers, who trust and rely on us to be part of their success over the long term.

(For more details on TSMC's Core Values, please visit:https://www.tsmc.com/english/aboutTSMC/values)

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