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Entry Level Ai Developer Jobs in Georgia (NOW HIRING)

Software Developer - Entry Level Category: Software Development/ Engineering Main location: United ... You'll gain hands-on experience with modern development practices and AI-enabled workflows while ...

In this role at PwC, you will apply data, algorithms, and software engineering to build and deploy ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

... and modify engineering drawingsStrong communication skillsAble to work in a team ... Entry Level Job Type & Location This is a Contract to Hire position based out of Atlanta, GA. Pay ...

This is an entry-level engineering role ideal for someone eager to grow their skills while contributing to high-quality slot game experiences. We are actively seeking candidates who use AI-assisted ...

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Entry Level Ai Developer information

See Georgia salary details

$24.9K

$84.7K

$203.9K

How much do entry level ai developer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for entry level ai developer in Georgia is $84,662.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,600.00 and $89,500.00 per year, depending on experience, location, and employer.

What does an entry level AI developer do?

An Entry Level AI Developer assists in designing, developing, and implementing artificial intelligence models and systems under the guidance of senior engineers. Their responsibilities often include data preprocessing, coding algorithms, testing AI solutions, and collaborating with cross-functional teams. They typically work with programming languages like Python, utilize machine learning libraries, and help improve model accuracy. This role provides foundational experience for building a career in AI and machine learning.

What types of projects and tasks can an entry level AI developer expect to work on in their first year?

As an Entry Level AI Developer, you can expect to work on a variety of foundational tasks such as data preprocessing, implementing and testing machine learning models, and supporting senior developers with code maintenance. You may be involved in gathering and cleaning data, conducting exploratory data analysis, and assisting with model evaluation and performance tuning. Collaboration with data scientists, engineers, and product teams is common, as you’ll help integrate AI solutions into existing systems or applications. This hands-on experience is valuable for building technical skills and understanding the full AI development lifecycle.

What are the key skills and qualifications needed to thrive as an entry level AI developer, and why are they important?

To thrive as an Entry Level AI Developer, you need a solid grasp of programming languages like Python, foundational knowledge in mathematics and statistics, and a relevant degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), version control systems (like Git), and cloud platforms is typically expected. Strong problem-solving skills, teamwork, and a willingness to learn are crucial soft skills for this role. These competencies enable you to contribute effectively to AI projects, adapt to evolving technologies, and collaborate well with multidisciplinary teams.

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

AspectEntry Level Ai DeveloperData Analyst
Required CredentialsBachelor's in CS, AI, or related field; knowledge of programming languages like PythonBachelor's in Statistics, Math, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentTech companies, AI startups, R&D departmentsBusiness, finance, healthcare, and marketing sectors
Employer & Industry UsageDevelop AI models, machine learning algorithms, and automation toolsAnalyze data trends, generate reports, and support decision-making

While both roles require strong analytical skills and programming knowledge, Entry Level Ai Developers focus on creating AI models and algorithms, often in tech-driven environments. Data Analysts interpret data to inform business decisions, working across various industries. The roles overlap in data handling and technical skills but differ in their core objectives and tools used.

What are the most commonly searched types of Ai Developer jobs in Georgia?

The most popular types of Ai Developer jobs in Georgia are:

What job categories do people searching Entry Level Ai Developer jobs in Georgia look for?

The top searched job categories for Entry Level Ai Developer jobs in Georgia are:

What cities in Georgia are hiring for Entry Level Ai Developer jobs?

Cities in Georgia with the most Entry Level Ai Developer job openings:

Infographic showing various Entry Level Ai Developer job openings in Georgia as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $84,662 per year, or $40.7 per hour.

Data Scientist /data analyst entry level /AI /software programmer(Remote)

SC Works Trident

Savannah, GA • On-site

$55 - $75/hr

Other

Posted 4 days ago


Job description

Data Scientist /data analyst entry level /AI /software programmer(Remote)

Occupation: Data Scientists Location: Savannah, GA - 31401 Job Type: Full Time (30 Hours or More) Posted: 03/23/2026

Positions available: 1 Source: SynergisticIT Web Site: www.synergisticit.com Onsite / Remote: Work at home all of the time

Job #: 24-02321

Type of Job: Not Available Full or Part Time: Full Time (30 Hours or More) Job Duration: Not Available

Minimum Experience Required: Not Available

Minimum Education Level Required: Not Available Required License/Certification: Not Available

Occupation Information for Data Scientists

Data Scientists - Develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software. Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets. Visualize, interpret, and report data findings. May create dynamic data reports.

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