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Entry Level Ai Computer Science Jobs in Raleigh, NC

Qualifications • Bachelor's degree in Data Science, Computer Science, Statistics, Public Policy, or related field; Master's preferred. • 2+ years of hands-on experience with data analysis, AI ...

What We Look For In a Computer Programming Tutor * Advanced Subject Mastery: Deep knowledge of ... advanced technology, AI, and the latest in learning science to create personalized learning ...

What We Look For In a Computer Programming Tutor * Advanced Subject Mastery: Deep knowledge of ... advanced technology, AI, and the latest in learning science to create personalized learning ...

Embedded Data Scientist

Morrisville, NC · On-site

$130K - $150K/yr

Become a Key Player as an Embedded Data Scientist You will develop and package AI models for ... Bachelor's degree in Mathematics, Data Science, Computer Science, Computer Engineering, or a ...

Are you fascinated by how AI and robots perceive the world? We're looking for energetic, outgoing ... Interest in Computer Science, Robotics, Engineering, or Marketing * Experience in street teaming ...

Senior Data Scientist II

Raleigh, NC · On-site

$104K - $174K/yr

Mentor team members and provide technical leadership in data science and AI. Requirements: * Master's degree or above in a quantitative or technical field (Statistics, Computer Science, Mathematics ...

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Entry Level Ai Computer Science information

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$28.7K

$97.5K

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How much do entry level ai computer science jobs pay per year?

As of Jul 11, 2026, the average yearly pay for entry level ai computer science in Raleigh, NC is $97,466.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,700.00 and $103,000.00 per year, depending on experience, location, and employer.

What are entry level AI computer science jobs?

Entry level AI computer science jobs are positions designed for recent graduates or individuals with limited professional experience in artificial intelligence and computer science. These roles typically involve tasks such as data preprocessing, model training, testing algorithms, software development, and supporting senior engineers or researchers. Common job titles include AI Engineer, Machine Learning Engineer, Data Scientist, and AI Research Assistant. Entry level positions often require familiarity with programming languages like Python, basic knowledge of machine learning concepts, and experience working with data. These jobs provide an opportunity to build foundational skills and gain exposure to real-world AI applications.

What is the difference between Entry Level Ai Computer Science vs Data Analyst?

AspectEntry Level Ai Computer ScienceData Analyst
Required CredentialsBachelor's in CS, AI, or related field; basic programming skillsBachelor's in Statistics, Math, or related field; data analysis skills
Work EnvironmentTech companies, research labs, startups; focus on AI models and algorithmsBusiness, finance, healthcare; focus on interpreting data and generating reports
Employer & Industry UsageTech firms, AI startups, research institutionsCorporations, consulting firms, government agencies
Common Search & ComparisonEntry Level Ai Computer Science vs Data Analyst

Entry Level Ai Computer Science roles focus on developing AI models and algorithms, requiring programming and machine learning knowledge. Data Analysts interpret data to inform business decisions, emphasizing statistical analysis and reporting. While both roles work with data, AI roles are more technical and development-oriented, whereas Data Analysts focus on data interpretation and visualization.

Is AI taking entry-level computer science jobs?

Entry-level AI and computer science roles are growing as demand for AI skills, programming, and data analysis increases. However, these jobs typically require foundational knowledge in programming languages like Python, machine learning frameworks, and problem-solving skills, making them accessible to recent graduates with relevant training. Competition exists, but acquiring practical experience and certifications can improve job prospects.

What are the key skills and qualifications needed to thrive as an Entry Level AI Computer Scientist, and why are they important?

To thrive as an Entry Level AI Computer Scientist, you need a solid understanding of programming (especially Python), algorithms, and foundational knowledge in machine learning, typically supported by a degree in computer science or a related field. Familiarity with frameworks such as TensorFlow or PyTorch, experience with data analysis tools, and knowledge of version control systems like Git are commonly expected. Strong problem-solving skills, a collaborative mindset, and eagerness to learn make a candidate stand out in this rapidly evolving field. These skills are crucial for effectively building, testing, and deploying AI models while adapting to emerging technologies and team-driven projects.

What are good entry-level AI jobs?

Entry-level AI jobs include roles such as AI analyst, machine learning technician, data analyst, and research assistant, often requiring knowledge of programming languages like Python and familiarity with machine learning frameworks. These positions typically involve supporting AI development, data preprocessing, and model testing, and may require a bachelor's degree in computer science or related fields. Internships and apprenticeships in AI are also valuable starting points for gaining practical experience.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior AI researcher, machine learning director, or AI executive, often requiring advanced skills, extensive experience, and sometimes ownership of significant projects. These roles usually involve leadership, strategic planning, and expertise in tools like deep learning frameworks and data analysis. Compensation at this level reflects the value of specialized knowledge and impact on business outcomes.

Can I get an AI job with no experience?

Entry-level AI jobs often require some foundational knowledge of programming, machine learning concepts, and relevant tools like Python or TensorFlow. While prior experience is beneficial, candidates can improve their chances by completing online courses, certifications, or personal projects to demonstrate their skills. Employers may also consider internships or apprenticeships for those new to the field.

What are some typical projects or tasks an entry-level AI computer science professional might work on during their first year?

In an entry-level AI computer science role, you are likely to assist with tasks such as data preprocessing, implementing basic machine learning algorithms, and supporting model evaluation efforts. You may also contribute to developing or maintaining codebases for AI applications, preparing datasets, or running experiments under the guidance of senior team members. Collaboration is common—you’ll often work with data scientists, software engineers, and product managers to support larger projects and gain exposure to the full AI development lifecycle. These experiences provide a solid foundation for advancing to more complex responsibilities over time.
What are the most commonly searched types of Ai Computer Science jobs in Raleigh, NC? The most popular types of Ai Computer Science jobs in Raleigh, NC are:
What are popular job titles related to Entry Level Ai Computer Science jobs in Raleigh, NC? For Entry Level Ai Computer Science jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Entry Level Ai Computer Science jobs in Raleigh, NC look for? The top searched job categories for Entry Level Ai Computer Science jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Entry Level Ai Computer Science jobs? Cities near Raleigh, NC with the most Entry Level Ai Computer Science job openings:
Trust & Safety Engineer (GenAI) - Remote

Trust & Safety Engineer (GenAI) - Remote

micro1 AI

Raleigh, NC • Remote

$50 - $90/hr

Part-time

Posted 11 days ago


Job description

Role Title: AI Jailbreak & Prompt-Injection Security Expert


Role Type: Contractor


Location: Remote


micro1 is engaging AI Jailbreak & Prompt-Injection Security Experts to contribute to a cutting-edge customer initiative focused on AI safety and robustness. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Design and implement advanced methodologies for evaluating AI system safety, focusing on ethical jailbreaks, LLM red teaming, prompt injection, and tool-use abuse scenarios.
  2. Create comprehensive cross-domain elicitation strategies to uncover multi-turn and complex adversarial bypass patterns in AI models.
  3. Develop, maintain, and update regression test suites that systematically test for jailbreak susceptibility and prompt-injection vulnerabilities.
  4. Construct robust evaluation frameworks that stress-test AI models against real-world adversarial threats, aiming to enhance overall system robustness.
  5. Collaborate with technical stakeholders to translate security findings into actionable improvements for model safety and risk mitigation.
  6. Document methodologies, findings, and best practices in clear, well-structured written reports and presentations for both technical and non-technical audiences.


Preferred Qualifications

  1. 2+ years of expertise in adversarial machine learning, LLM red teaming, AI safety evaluation, or a closely related security domain
  2. Proven experience researching, testing, or uncovering vulnerabilities related to ethical jailbreaks, prompt injection, tool-use abuse, or adversarial AI attacks.
  3. Advanced degree (PhD, MS) in computer science, cybersecurity, machine learning, or a relevant discipline, or equivalent operational/professional background.
  4. High credibility and recognition within the AI security or adversarial ML community—such as published research, open-source tools, or conference presentations.
  5. Exceptional written and verbal communication skills, with a strong focus on clear documentation and collaborative problem-solving.
  6. Prior participation in multi-disciplinary projects or cross-functional AI safety initiatives is a plus.
  7. Familiarity with current LLM architectures, prompt engineering techniques, and security assessment tools is highly desirable.