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Entry Level Ai Computer Science Jobs (NOW HIRING)

Join Galore Creative as an Entry-Level AI Content Writer and Ignite Your Career in the Exciting ... A Bachelor's degree in Communications, Journalism, Computer Science, or a closely related field.

Generative AI Analyst

New York, NY · On-site +1

$50K - $60K/yr

We seek an entry-level AI Analyst to join our team to research, prototype and implement AI ... Computer Science, Business, Data Science, or related field 0-2 years of professional experience ...

Thornton Tomasetti applies engineering and scientific principles to solve the world's challenges ... We have an opportunity for an AI & Computer Vision Intern for our Forensics Practice.

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

As of Jun 10, 2026, the average yearly pay for entry level ai computer science in the United States is $100,265.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,500.00 and $106,000.00 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.

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 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.
More about Entry Level Ai Computer Science jobs
What cities are hiring for Entry Level Ai Computer Science jobs? Cities with the most Entry Level Ai Computer Science job openings:
What are the most commonly searched types of Ai Computer Science jobs? The most popular types of Ai Computer Science jobs are:
What states have the most Entry Level Ai Computer Science jobs? States with the most job openings for Entry Level Ai Computer Science jobs include:

Copy of PhD Computer Science Expert for AI Training

Lifted, an Upwork Company™

California City, CA • Remote

$150/hr

Contractor

Posted 14 days ago


Job description

Company Description

An enterprise client is seeking highly technical Computer Science Experts with PhDs to support the training and evaluation of advanced AI models. This initiative focuses on improving the accuracy, reasoning, and domain expertise of generative AI systems through expert human feedback.

The selected candidates will contribute to the company's large AI training project by evaluating AI-generated responses, developing domain-specific prompts, and assessing technical accuracy across complex Computer Science topics. This is a fully remote, freelance opportunity with flexible working hours and the potential for ongoing work beyond the initial project timeline.

    Job Description

    This opportunity is ideal for highly analytical professionals with advanced academic or industry experience in Computer Science or related technical fields.

    What You'll Do:

    • Assess the factual accuracy, relevance, and quality of AI-generated Computer Science content
    • Craft and answer domain-specific questions related to Computer Science and adjacent technical disciplines
    • Evaluate and rank AI-generated responses based on technical correctness and reasoning quality
    • Provide expert-level feedback to improve AI model performance and domain understanding
    • Support AI training initiatives by applying research, analytical thinking, and technical expertise

    This role is a strong fit for professionals with backgrounds in:

    • Computer Science
    • Software Engineering
    • Machine Learning
    • Cybersecurity
    • Distributed Systems
    • Computational Science
    • Information Theory
    • Quantitative Finance (highly preferred)
    • Statistics
    • Electrical & Computer Engineering
    • Technical Research or Academia
    Qualifications

    Requirements:

    • Native or fluent English communication skills (written and verbal)
    • PhD in Computer Science or a closely related technical field
    • Experience working as a software engineer, researcher, or in another highly technical or analytical role
    • Strong technical reasoning and attention to detail
    • Ability to assess complex AI-generated technical outputs with accuracy and consistency

    Nice to Haves:

    • Strong academic or industry research background
    • Experience reviewing technical content, publications, or research outputs
    • Familiarity with AI systems, large language models, or AI evaluation workflows
    • Experience in advanced Computer Science domains such as machine learning, distributed systems, or cybersecurity
    Additional Information
    • Fully remote freelance opportunity with flexible working hours
    • Work is expected to begin immediately and continue through the end of June, with potential extensions
    • Compensation: Up to $150 USD per hour based on project participation
    • Weekly lump-sum payments issued for completed work tracked within the client platform
    • No guaranteed hours or task volume; work availability may vary weekly
    • Candidates must be physically located in one of the following regions: United States, Canada, Puerto Rico, Mexico, Great Britain, Australia, New Zealand, or Argentina
    • Selected candidates will receive onboarding instructions and platform access after acceptance
    • Candidates should not independently create an Outlier profile prior to onboarding