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Generative Ai Junior Jobs (NOW HIRING)

Georgia IT, Inc.

Generative AI Architect - Remote

$64.50 - $85/hr

... to junior team members and foster a culture of continuous learning within the AI team ... generative AI models and solutions. • Hands-on experience with AI frameworks and tools such as ...

Saransh Inc

Junior Gen AI Engineer

Santa Clara, CA · On-site

Role: Junior GenAI Engineer Location: Santa Clara, CA (Onsite from Day 1) Job Type: Contract ... Implement and manipulate complex algorithms essential for developing and optimizing generative AI ...

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How much do generative ai junior jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for generative ai junior in the United States is $26.96, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $33.17 per hour, depending on experience, location, and employer.

What does a generative AI junior do?

A Generative AI Junior assists in developing and implementing artificial intelligence models, particularly those focused on generating content such as text, images, or music. They typically support senior engineers or data scientists by preparing datasets, running experiments, and evaluating model outputs. Their role may also include troubleshooting issues, optimizing model performance, and staying updated with the latest advancements in AI. This position is ideal for individuals starting their careers in AI and interested in hands-on experience with generative models.

What are the key skills and qualifications needed to thrive as a generative AI junior, and why are they important?

To thrive as a Generative AI Junior, you need a solid understanding of machine learning fundamentals, basic programming skills (especially in Python), and a relevant degree in computer science or a related field. Familiarity with AI frameworks like TensorFlow or PyTorch, and experience using version control systems such as Git, are typically expected. Strong problem-solving abilities, eagerness to learn, and effective teamwork are crucial soft skills in this role. These competencies are vital for effectively supporting AI projects, adapting to rapidly evolving technologies, and collaborating within multidisciplinary teams.

What are some common challenges faced by a generative AI junior, and how can they be overcome?

As a Generative AI Junior, you may encounter challenges such as staying updated with rapidly evolving AI technologies, understanding complex machine learning frameworks, and managing the quality of generated outputs. Overcoming these hurdles often involves continuous learning through online courses and mentorship, actively participating in code reviews, and collaborating closely with senior AI engineers and data scientists. Building a habit of documenting your experiments and results can also help you track progress and learn from setbacks.

What is the difference between Generative Ai Junior vs Data Scientist?

AspectGenerative Ai JuniorData Scientist
Required CredentialsBachelor's in CS, AI, or related field; basic understanding of MLBachelor's or higher in CS, Data Science, or related; advanced ML knowledge
Work EnvironmentTech companies, AI startups, R&D teamsData-driven organizations, tech firms, consulting
Employer & Industry UsageAI development, research projects, product teamsData analysis, predictive modeling, business insights

Generative Ai Junior roles focus on assisting in developing AI models that generate content, requiring foundational AI knowledge. Data Scientists analyze data and build models for insights. While both work in AI and data fields, Generative Ai Juniors typically have less experience and focus on generative models, whereas Data Scientists handle broader data analysis and modeling tasks.

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Generative Ai Junior jobs near you
Infographic showing various Generative Ai Junior job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 76% Full Time, 19% Part Time, and 4% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $56,068 per year, or $27 per hour.

Generative AI Architect

Jersey City, NJ • Hybrid

TekPioneers - A TekGence Company
See more jobs at TekPioneers - A TekGence Companyexternal

$69 - $90.75/hr

Full-time

Posted 26 days ago

Job description

Job Title: Generative AI Architect
Position Type: Contract
Location: Jersey City, NJ (Hybrid)
 
Position Overview
We are seeking a highly skilled and experienced Generative AI (GenAI) Onsite Architect to join our team. The ideal candidate should have a deep understanding of AI technologies, particularly in the area of generative AI models, and will be responsible for designing and implementing AI solutions.
Key Responsibilities:
• Develop and design scalable and efficient GenAI solutions tailored to our requirements.
• Lead the implementation of GenAI systems, ensuring they are robust, secure, and performant.
• Work closely with cross-functional teams, including engineers and product managers to integrate AI solutions into existing systems.
• Stay up-to-date with the latest advancements in AI and apply this knowledge to drive innovation within the company.
• Create comprehensive documentation for AI solutions, including design specifications, implementation guides, and user manuals.
• Provide training and mentorship to junior team members and clients on GenAI technologies and best practices.
Qualifications:
• Minimum of 5 years of experience in AI/ML, with a focus on generative models.
• Proven track record of successfully implementing AI projects in real-world settings. Experience in managing the end-to-end lifecycle of AI projects, from conception to deployment.
• Proficiency in programming languages such as Python and other AI frameworks.
• Strong analytical and problem-solving skills, with the ability to think critically and creatively.
• Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
• Proven leadership abilities, with experience managing and mentoring technical teams.
• Ability to work in a fast-paced, dynamic environment and adapt to changing project requirements.
• Experience with cloud platforms such as AWS.
• Familiarity with natural language processing (NLP)
Preferred Qualifications: 
Familiarity with DevOps practices and CI/CD pipelines for automated software deployment and delivery