Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment ...
Artificial Intelligence (AI) Engineer I
$106K - $127K/yr
Artificial Intelligence (AI) Engineer I Melbourne, FL 12 Months Position Summary: An AI (Artificial Intelligence) Engineer develops and trains AI models to automate processes and solve complex ...
Artificial Intelligence (AI) Engineer I
$106K - $127K/yr
Artificial Intelligence (AI) Engineer I Melbourne, FL 12 Months Position Summary: An AI (Artificial Intelligence) Engineer develops and trains AI models to automate processes and solve complex ...
Entry Level Artificial intelligence security specialist
$16.50 - $22.25/hr
Currently, We are looking for entry-level software programmers, IT enthusiasts, Python/Java developers, Data analysts/ Data Scientists. We welcome candidates with all visas and citizens to apply. Who ...
Entry Level Artificial intelligence security specialist
$16.50 - $22.25/hr
Currently, We are looking for entry-level software programmers, IT enthusiasts, Python/Java developers, Data analysts/ Data Scientists. We welcome candidates with all visas and citizens to apply. Who ...
Artificial Intelligence Engineer II
Houston, TX · On-site
$109K - $131K/yr
Baylor College of Medicine is looking for an experienced Artificial Intelligence Engineer II to support Dr. Ihab Hajjar. In this role, you will develop and evaluate machine learning and natural ...
Artificial Intelligence Engineer II
Houston, TX · On-site
$109K - $131K/yr
Baylor College of Medicine is looking for an experienced Artificial Intelligence Engineer II to support Dr. Ihab Hajjar. In this role, you will develop and evaluate machine learning and natural ...
Entry Level Artificial intelligence security specialist
$16.25 - $21.50/hr
Who Should Apply Recent Computer science/Engineering /Mathematics/Statistics or Science Graduates ... entry level position the additional skills and Project work with hands on experience building ...
Entry Level Artificial intelligence security specialist
$16.25 - $21.50/hr
Who Should Apply Recent Computer science/Engineering /Mathematics/Statistics or Science Graduates ... entry level position the additional skills and Project work with hands on experience building ...
Entry Level Artificial Intelligence Engineer information
See salary details
$30K - $38K
2% of jobs
$38K - $46K
10% of jobs
$51.3K is the 25th percentile. Wages below this are outliers.
$46K - $54K
20% of jobs
$54K - $62K
13% of jobs
The median wage is $64K / yr.
$62K - $70K
21% of jobs
$75.2K is the 75th percentile. Wages above this are outliers.
$70K - $78K
14% of jobs
$78K - $86K
7% of jobs
$86K - $94K
5% of jobs
$94K - $102K
3% of jobs
$102K - $110K
2% of jobs
$110K - $118K
2% of jobs
$30K
$69.4K
$118K
How much do entry level artificial intelligence engineer jobs pay per year?
As of Jun 9, 2026, the average yearly pay for entry level artificial intelligence engineer in the United States is $69,362.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,500.00 and $78,500.00 per year, depending on experience, location, and employer.
What kind of projects or tasks do Entry Level Artificial Intelligence Engineers typically work on?
Entry Level Artificial Intelligence Engineers often assist with data collection and preprocessing, implement and test machine learning models, and support research or production teams in developing AI solutions. You may help analyze large datasets, tune model parameters, write scripts for automation, and contribute to code reviews or documentation. Collaboration is common, as you’ll often work closely with data scientists, senior AI engineers, and product managers to advance ongoing projects. These experiences provide a strong foundation for developing your technical skills and understanding how AI solutions are built and deployed in real business environments.
What are the key skills and qualifications needed to thrive in the Entry Level Artificial Intelligence Engineer position, and why are they important?
To thrive as an Entry Level Artificial Intelligence Engineer, you need a solid background in programming (especially Python), mathematics (linear algebra, statistics), and foundational machine learning concepts, often demonstrated through a relevant degree or project experience. Familiarity with key AI frameworks such as TensorFlow or PyTorch, version control systems like Git, and optionally certifications like Google’s TensorFlow Developer Certificate are valuable assets. Strong problem-solving skills, curiosity, and the ability to collaborate and communicate clearly within teams will help you stand out. These competencies are crucial for contributing effectively to real-world AI projects, learning on the job, and advancing in this rapidly evolving field.
What is an Entry Level Artificial Intelligence Engineer job?
An Entry Level Artificial Intelligence Engineer is responsible for developing AI models, writing algorithms, and working with data to build intelligent systems. They typically assist in training machine learning models, optimizing performance, and integrating AI solutions into applications. This role requires knowledge of programming languages like Python, machine learning frameworks, and data processing techniques. Entry-level AI engineers often collaborate with data scientists and software engineers to improve AI functionalities. Employers usually look for candidates with a degree in computer science, engineering, or a related field, along with hands-on experience in AI projects.
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Job description
Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment about deterministic versus model-driven system boundaries Experience with human review, escalation, auditability, and operational safeguards Willingness to work closely with teams to understand real workflows, not just stated requirements built internal platforms, shared services, or workflow systems used by multiple teams designed connectors, integration patterns, tool contracts, or context layers built AI systems for enterprise operations, security-sensitive workflows, compliance-heavy domains, or internal business processes Practical daily use of LLMs as building tools
About InfoPeople
Sourced by ZipRecruiter
Industry
Recruiting and staffing services
Company size
11 - 50 Employees
Headquarters location
New York, NY, US
Year founded
1998