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Generative Ai Developer Jobs in Arkansas (NOW HIRING)

Rishabh Software Pvt. Ltd

AI Engineer

Little Rock, AR · On-site

$109K - $131K/yr

AI Engineer Location: Carmel, IN, Little Rock, AR & Eagan, MN (Hybrid) Duration: Contract to hire ... Research and prototype AI/ML models in areas such as NLP, computer vision, generative AI, and ...

Pwc

AI Engineer

Little Rock, AR · On-site

$50K - $112K/yr

... generative AI techniques, including prompt engineering, LLM evaluation, and fine-tuning, to develop production-ready applications powered by foundation models - Developing automated evaluation ...

Pwc

AI Engineer

Fayetteville, AR · On-site

$50K - $112K/yr

... generative AI techniques, including prompt engineering, LLM evaluation, and fine-tuning, to develop production-ready applications powered by foundation models - Developing automated evaluation ...

Triunity Software

AI Engineer

Little Rock, AR · On-site

$100K - $110K/yr

Triunity Software is looking for a talented and driven AI Engineer to join our growing team in ... Experience with NLP, computer vision, or generative AI is a strong plus * Familiarity with cloud ...

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Generative Ai Developer information

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$15

$37

$83

How much do generative ai developer jobs pay per hour?

As of Sep 1, 2026, the average hourly pay for generative ai developer in Arkansas is $37.45, according to ZipRecruiter salary data. Most workers in this role earn between $19.47 and $45.34 per hour, depending on experience, location, and employer.

What is a generative AI developer?

A Generative AI Developer is a technology professional who specializes in designing, building, and deploying artificial intelligence systems that can create new content, such as text, images, audio, or code. They work with advanced machine learning models, like generative adversarial networks (GANs) or large language models, to enable computers to produce original outputs. These developers often collaborate with data scientists, researchers, and product teams to integrate AI-generated content into software applications and business solutions.

What are the key skills and qualifications needed to thrive as a generative AI developer?

To thrive as a Generative AI Developer, you need strong programming skills (especially in Python), a deep understanding of machine learning concepts, and an advanced degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and experience with cloud platforms or model deployment tools are typically required. Creative problem-solving, adaptability, and effective collaboration are standout soft skills in this evolving field. These abilities are crucial to design, implement, and refine generative models that solve real-world problems and drive innovation.

What are some common challenges faced by generative AI developers when deploying models in production environments?

Generative AI Developers often encounter challenges such as ensuring model reliability, managing computational resource requirements, and addressing ethical considerations like data bias or content safety. Deploying generative models at scale requires robust monitoring to detect unexpected outputs or model drift, and collaboration with data engineers and product teams to optimize performance. Staying up-to-date with evolving frameworks and best practices is essential, as production environments demand both technical rigor and adaptability to new AI advancements.

What is the difference between Generative Ai Developer vs Machine Learning Engineer?

AspectGenerative Ai DeveloperMachine Learning Engineer
CredentialsBachelor's or higher in CS, AI, or related fields; experience with deep learning frameworksBachelor's or higher in CS, Data Science, or related fields; strong programming skills
Work EnvironmentDevelops AI models for content creation, chatbots, and creative applicationsBuilds and deploys ML models for various data-driven solutions across industries
Industry UsageTech, entertainment, marketing, and creative sectorsFinance, healthcare, tech, and e-commerce sectors

While both roles involve AI and machine learning, Generative Ai Developers focus on creating models that generate content, such as images or text, whereas Machine Learning Engineers develop broader ML solutions for diverse applications. The roles often overlap but differ mainly in their specific focus areas and use cases.

How to become a generative AI developer?

To become a generative AI developer, you should have a strong foundation in programming languages like Python, experience with machine learning frameworks such as TensorFlow or PyTorch, and knowledge of neural network architectures like transformers. Gaining expertise in natural language processing and deep learning, along with practical experience through projects or internships, is essential. Certifications in AI or data science can also enhance your qualifications.

What are popular job titles related to Generative Ai Developer jobs in Arkansas?

For Generative Ai Developer jobs in Arkansas, the most frequently searched job titles are:

What job categories do people searching Generative Ai Developer jobs in Arkansas look for?

The top searched job categories for Generative Ai Developer jobs in Arkansas are:

What cities in Arkansas are hiring for Generative Ai Developer jobs?

Cities in Arkansas with the most Generative Ai Developer job openings:

Generative Ai Developer jobs near you
Infographic showing various Generative Ai Developer job openings in Arkansas as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 72% Physical, 3% Hybrid, and 25% Remote job distribution, with an average salary of $77,894 per year, or $37.4 per hour.

AI Engineer

Rishabh Software Pvt. Ltd

Little Rock, AR • On-site

$109K - $131K/yr

Other

Re-posted 5 days ago

Job description

Position: AI Engineer

Location: Carmel, IN, Little Rock, AR & Eagan, MN (Hybrid)

Duration: Contract to hire (6 months)

Responsibilities:

  • Research and prototype AI/ML models in areas such as NLP, computer vision, generative AI, and recommendation systems. Rapidly test new tools, frameworks, and APIs (e.g., OpenAI, Hugging Face, Google Vertex AI) for use in forward-looking applications.
  • Engage in ideation sessions and support the development of MVPs and scalable solutions.
  • Utilize a variety of programming languages and tools to build and deploy machine learning models.
  • Support both batch and real-time inference pipelines in collaboration with Data Science and Applied AI teams.
  • Support the development of MVP Gen AI applications by enabling data integrations, vendor connections, and deployment paths Assist in building custom deployment workflows in Python (e.g., with Kubernetes or REST APIs) when needed for prioritized prototypes
  • Collaborate closely to integrate AI into user-facing interfaces Use APIs (e.g., OpenAI, Hugging Face) to embed intelligent features. Ability to make timely recommendations to effectively solve problems, using independent judgment consistent with standards, practices, policies, procedures, regulations, and/or law.

Requirement:

  • Bachelor's degree in, Computer Science, Computer Information Systems, IT, Software Engineering, Data Analytics, Data Science OR Mathematics, Statistics, Economics, Business Administration, or related field with Equivalent Masters or Certifications and see level years of experience (required)
  • Masters, PhD, or Advanced degree (Preferred)
  • 3+ years of experience in AI/ML engineering (Preferred)
  • Experience working with generative AI (e.g., LLMs, diffusion models, multimodal models) preferred
  • Specific experience with R and Python (Required)
  • Previous energy industry experience (Preferred)
  • Specific experience with 5-7 of the following required: Predictive Modelling, Data Cleaning, Data Visualization, Segmentation Modelling, Natural Language Processing, Graph Database Knowledge, API Usage, Database Querying, Software Development, Applied Mathematical Modelling, Programming for Automation, Data Pipeline Building, CI/CD
  • Azure Certifications preferred

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