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Entry Level Computer Science Artificial Intelligence Jobs in Los Angeles, CA

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Entry Level Computer Science Artificial Intelligence information

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How much do entry level computer science artificial intelligence jobs pay per hour?

As of Aug 29, 2026, the average hourly pay for entry level computer science artificial intelligence in Los Angeles, CA is $18.23, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $18.65 per hour, depending on experience, location, and employer.

What is an entry level computer science artificial intelligence job?

Entry Level Computer Science Artificial Intelligence jobs are positions designed for recent graduates or individuals with limited professional experience in computer science, specifically focusing on artificial intelligence (AI). These roles typically involve assisting in the development, testing, and deployment of AI models and algorithms under the guidance of more experienced engineers or data scientists. Tasks may include data preprocessing, writing code for machine learning models, evaluating model performance, and collaborating with teams to solve real-world problems using AI. Entry-level AI jobs provide an opportunity to gain practical experience, learn industry-standard tools and frameworks, and build foundational skills for a career in artificial intelligence.

What types of projects can I expect to work on as an entry level computer science artificial intelligence professional?

As an entry-level AI professional, you’ll typically contribute to projects involving data preprocessing, model training, and algorithm implementation under the guidance of senior team members. You might work on tasks like cleaning datasets, developing and testing machine learning models, and assisting in deploying AI solutions. Collaboration with software engineers, data scientists, and product managers is common, providing you with a well-rounded introduction to real-world AI development and teamwork. These projects help you build foundational skills while gaining exposure to various AI applications and industry tools.

What are the key skills and qualifications needed to thrive as an entry level computer science artificial intelligence professional?

To excel in an entry-level AI role, you need a solid understanding of computer science fundamentals, programming languages like Python, and basic knowledge of algorithms and data structures, typically supported by a relevant degree. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), data analysis tools, and version control systems is highly valued. Strong problem-solving skills, curiosity, and effective teamwork set candidates apart in this field. These abilities are crucial for building robust AI solutions, adapting to technological advances, and collaborating efficiently on complex projects.

What is the difference between Entry Level Computer Science Artificial Intelligence vs Entry Level Data Science?

AspectEntry Level Computer Science Artificial IntelligenceEntry Level Data Science
Required CredentialsBachelor's in Computer Science, AI, or related fields; knowledge of programming, machine learning, and algorithmsBachelor's in Data Science, Statistics, or related fields; skills in programming, statistics, and data analysis
Work EnvironmentTech companies, research labs, startups focusing on AI applicationsBusiness, finance, healthcare, and tech firms analyzing data for insights
Employer & Industry UsageUsed in AI development, machine learning projects, and automationUsed in data analysis, predictive modeling, and business intelligence

Both roles require programming skills and a strong foundation in computer science. While AI focuses on developing intelligent systems and algorithms, data science emphasizes analyzing data to inform decisions. The choice depends on your interest in creating AI solutions versus extracting insights from data.

Can I get an entry level computer science artificial intelligence job with no experience?

Entry level computer science artificial intelligence positions often require some foundational knowledge in programming, algorithms, and machine learning, but many employers consider candidates with relevant coursework, personal projects, or certifications even without formal work experience. Building skills in languages like Python and tools such as TensorFlow can improve your chances, and internships or online courses can help demonstrate your abilities to employers.

Is artificial intelligence taking entry-level computer science jobs?

Entry-level computer science jobs involving artificial intelligence are growing as companies seek new talent with skills in machine learning, programming, and data analysis. However, competition remains high, and candidates often need foundational knowledge in programming languages like Python and familiarity with AI frameworks to succeed.

What are popular job titles related to Entry Level Computer Science Artificial Intelligence jobs in Los Angeles, CA?

For Entry Level Computer Science Artificial Intelligence jobs in Los Angeles, CA, the most frequently searched job titles are:

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The top searched job categories for Entry Level Computer Science Artificial Intelligence jobs in Los Angeles, CA are:

What cities near Los Angeles, CA are hiring for Entry Level Computer Science Artificial Intelligence jobs?

Cities near Los Angeles, CA with the most Entry Level Computer Science Artificial Intelligence job openings:

Infographic showing various Entry Level Computer Science Artificial Intelligence job openings in Los Angeles, CA as of June 2026, with employment types broken down into 56% Full Time, 39% Part Time, 1% Temporary, 2% Contract, and 2% Nights. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $37,928 per year, or $18.2 per hour.

Artificial Intelligence

Los Angeles, CA • On-site

BridgeNexus Technologies Inc
IT Services • 11 - 50 employees

Other

Posted 22 days ago


Job description

Hi, WE have below 2 positions with our direct client and both are hybrid position and kindly reply asap at your interest so I reach you immediately to schedule one round interview with client .
 
JOB 1:  AI Analyst with Healthcare Background
Location: Woodland Hills. CA (Commute three times in a week to Woodland Hills office)
Duration: Long term
Client: Direct client
JOB 2: AI ML Developer with Data Science experience
Location: Woodland Hills. CA (Commute three times in a week to Woodland Hills office)
Duration: Long term
Client: Direct client 
 
 
 
 
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Role
Job Description
1
AI Analyst with Healthcare Background
seeking an experienced Artificial Intelligence & Machine Learning (AI/ML) Systems Analyst to bridge the gap between business stakeholders, data scientists, AI/ML engineers, and technology teams. This role will be responsible for analyzing business problems, defining AI/ML solution requirements, evaluating data readiness, supporting model implementation, and ensuring AI solutions align with business objectives, regulatory requirements, and enterprise governance standards. The ideal candidate will possess strong analytical skills, healthcare domain knowledge, and experience working with AI, machine learning, and Generative AI technologies.

Key Responsibilities
Business & Systems Analysis
  • Collaborate with business stakeholders to identify opportunities for AI/ML-driven process improvements and automation.
  • Elicit, analyze, and document business, functional, and non-functional requirements.
  • Create user stories, process flows, use cases, data mappings, and acceptance criteria.
  • Translate business requirements into AI/ML solution specifications.
  • Support backlog grooming, sprint planning, and Agile delivery processes.
AI/ML Solution Analysis
  • Partner with AI/ML engineers and data scientists to define model objectives and success metrics.
  • Analyze data sources and determine data quality, completeness, and readiness for AI initiatives.
  • Support predictive analytics, recommendation systems, NLP, GenAI, and intelligent automation initiatives.
  • Evaluate AI model outputs and assist with validation, testing, explainability, and business adoption.
Data & Analytics