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Full Time Machine Learning Data Annotation Jobs in Raleigh, NC

The company employs over 2,000 technologists, data scientists, and experts to develop, test, and ... We are seeking a Principal Machine Learning Engineer to design, build, and operate scalable AI/ML ...

The role requires expertise in predictive modeling and big data analytics, with a focus on implementing machine learning techniques to solve various business problems in the banking and financial ...

Applied Machine Learning Engineer

Durham, NC · On-site

$110K - $132K/yr

As the Data Engineer, you will design and build the data infrastructure that makes Vulcan's operational and business data useful -- first at pilot scale, and then as the foundation for a 10,000 ton ...

They are seeking a Senior Data Scientist to lead AI and machine learning model development, analyze large datasets, and mentor junior team members. Responsibilities : • Working closely with other ...

They are seeking a Senior Data Scientist to lead AI and machine learning model development, analyze large datasets, and mentor junior team members. Responsibilities : • Working closely with other ...

MANAGER, DATA SCIENCE The Manager of Data Science will build and lead a focused, high-impact team ... Experience applying machine learning in real-world business settings Skills: * Strong problem ...

A specialization in machine-learning, artificial intelligence, cognitive science or data science is preferred. Must be self-driven, curious and creative. * Experience must include creating and using ...

Showing results 21-40

Full Time Machine Learning Data Annotation information

See Raleigh, NC salary details

$36.5K

$119.3K

$191K

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

As of Sep 2, 2026, the average yearly pay for full time machine learning data annotation in Raleigh, NC is $119,312.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,800.00 and $132,200.00 per year, depending on experience, location, and employer.

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 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 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 popular job titles related to Full Time Machine Learning Data Annotation jobs in Raleigh, NC?

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

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

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

Infographic showing various Full Time Machine Learning Data Annotation job openings in Raleigh, NC as of July 2026, with employment types broken down into 19% Full Time, 6% Part Time, 69% Contract, and 6% Nights. Highlights an 4% Physical, and 96% Remote job distribution, with an average salary of $119,312 per year, or $57.4 per hour.

Cyber Digital Trust & Online Safety Manager

Deloitte

Raleigh, NC

Full-time

Re-posted 12 days ago


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 93 frontline employees who took The Breakroom Quiz

46th of 152 rated financial services


Job description

Cyber Digital Trust and Online Safety Manager

The Digital Trust & Online Protection Professional will advise clients in developing, managing, and implementing policies, procedures, and strategies to ensure a safe, compliant, and trustworthy environment for our users. This individual will scale and mature digital trust and safety processes, including content compliance, user protection, and regulatory adherence across our platforms for our clients. Working closely with cross-functional stakeholders, this role will monitor regulatory changes, manage risks, and enhance our organization's approach to content safety, user trust, and online integrity.

Recruiting for this role ends on 12/31/3026.

Work you'll do

As a Manager, Strategy, Growth, and Transformation on the Deloitte Cyber team, you will be responsible for:

  • Designing and executing testing scenarios to identify how prompts or user inputs could be manipulated to generate harmful, misleading, or misaligned generative artificial intelligence outputs.
  • Researching emerging prompt injection, jailbreak, and adversarial testing techniques to evaluate model weaknesses, bias, factual inaccuracy, and misalignment with user intent.
  • Assessing the effectiveness of content moderation systems in detecting unsafe outputs and documenting vulnerabilities, failure patterns, and potential misuse impacts.
  • Recommending improvements to moderation policies, flagging mechanisms, training data, and governance controls based on testing findings.
  • Collaborating with generative artificial intelligence development, content moderation, and cross-functional stakeholders to strengthen security, trust, safety, and responsible use outcomes.
  • Developing multimodal test content and novel prompt manipulation methods to identify failure modes across text and other model inputs.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

The team

Enables trust and safety of online communications and digital products, protecting users, consumers, and patients from harm. Enables clients to provide consumer confidence in knowing with whom they are dealing and ensuring the integrity of access to data.

Qualifications

Required:

  • Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Cybersecurity, Linguistics, Psychology, or a related field, or equivalent professional experience
  • 10+ years of experience in threat modeling and simulation, prompt generation and analysis, novel testing, and reporting and improvement
  • Demonstrated hands-on experience, portfolio work, publications, or research in prompt injection, jailbreak testing, model evaluation, adversarial machine learning, multimodal artificial intelligence safety, or generative artificial intelligence vulnerability assessment
  • Ability to travel 25-50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Doctor of Philosophy (PhD) in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Cybersecurity, Linguistics, Psychology, or a related field, or equivalent professional experience
  • Specialized training or certifications in generative artificial intelligence red teaming, adversarial machine learning, artificial intelligence security, cybersecurity, responsible artificial intelligence, or artificial intelligence governance
  • Experience designing and operationalizing trust and safety testing programs for large-scale consumer platforms, including escalation workflows, issue triage, and remediation tracking
  • Experience working with product, legal, policy, and engineering stakeholders to translate risk findings into practical platform controls and governance improvements

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $134,500 to $265,100.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

#CyberDTP27

Qualifications:

Cyber Digital Trust and Online Safety Manager

The Digital Trust & Online Protection Professional will advise clients in developing, managing, and implementing policies, procedures, and strategies to ensure a safe, compliant, and trustworthy environment for our users. This individual will scale and mature digital trust and safety processes, including content compliance, user protection, and regulatory adherence across our platforms for our clients. Working closely with cross-functional stakeholders, this role will monitor regulatory changes, manage risks, and enhance our organization's approach to content safety, user trust, and online integrity.

Recruiting for this role ends on 12/31/3026.

Work you'll do

As a Manager, Strategy, Growth, and Transformation on the Deloitte Cyber team, you will be responsible for:

  • Designing and executing testing scenarios to identify how prompts or user inputs could be manipulated to generate harmful, misleading, or misaligned generative artificial intelligence outputs.
  • Researching emerging prompt injection, jailbreak, and adversarial testing techniques to evaluate model weaknesses, bias, factual inaccuracy, and misalignment with user intent.
  • Assessing the effectiveness of content moderation systems in detecting unsafe outputs and documenting vulnerabilities, failure patterns, and potential misuse impacts.
  • Recommending improvements to moderation policies, flagging mechanisms, training data, and governance controls based on testing findings.
  • Collaborating with generative artificial intelligence development, content moderation, and cross-functional stakeholders to strengthen security, trust, safety, and responsible use outcomes.
  • Developing multimodal test content and novel prompt manipulation methods to identify failure modes across text and other model inputs.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

The team

Enables trust and safety of online communications and digital products, protecting users, consumers, and patients from harm. Enables clients to provide consumer confidence in knowing with whom they are dealing and ensuring the integrity of access to data.

Qualifications

Required:

  • Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Cybersecurity, Linguistics, Psychology, or a related field, or equivalent professional experience
  • 10+ years of experience in threat modeling and simulation, prompt generation and analysis, novel testing, and reporting and improvement
  • Demonstrated hands-on experience, portfolio work, publications, or research in prompt injection, jailbreak testing, model evaluation, adversarial machine learning, multimodal artificial intelligence safety, or generative artificial intelligence vulnerability assessment
  • Ability to travel 25-50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Doctor of Philosophy (PhD) in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Cybersecurity, Linguistics, Psychology, or a related field, or equivalent professional experience
  • Specialized training or certifications in generative artificial intelligence red teaming, adversarial machine learning, artificial intelligence security, cybersecurity, responsible artificial intelligence, or artificial intelligence governance
  • Experience designing and operationalizing trust and safety testing programs for large-scale consumer platforms, including escalation workflows, issue triage, and remediation tracking
  • Experience working with product, legal, policy, and engineering stakeholders to translate risk findings into practical platform controls and governance improvements

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $134,500 to $265,100.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

#CyberDTP27

Education:Bachelor's DegreeEmployment Type:

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