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Ai Model Jobs in Delaware (NOW HIRING)

ClifyX

GenAI Engineer

Wilmington, DE · On-site

The role involves building and deploying models, ensuring compliance, and collaborating with various teams to enhance AI capabilities. Responsibilities : • Design and develop AI/ML and Generative ...

Morson Talent

AI Adoption Specialist

Wilmington, DE · On-site +1

$35 - $45/hr

Participate in prompt tuning and experimentation to improve model outputs. Assist with integrating AI services and models into applications and workflows using APIs. Build small prototypes, scripts ...

Luxoft

AI & Platform Software Engineer

Wilmington, DE · On-site

$110 - $150/hr

... model access via Azure AI Foundry today with a deliberately venue-agnostic design, model ... integrations, retrieval services, environments, observability) and the Developer Experience ...

Aumni

Applied AI/ML - Vice President

Wilmington, DE · On-site

$120 - $160/hr

  • Medical

  • Retirement

Implement monitoring mechanisms to track model performance in real-time and ensure model reliability. * Communicate AI/ML capabilities and results to both technical and non-technical audiences.

Barclays

VP - AI Risk Governance

Wilmington, DE · On-site

$180 - $240/hr

Join us as a VP - AI Risk Governance within Barclays' Model Risk Management function, where you will play a key role in advancing the responsible, ethical, and compliant use of artificial ...

Apex Systems

Generative AI Engineer

Newark, DE · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Utilize on-premises models and infrastructure to generate content and insights. * Leverage LLMs ... A minimum of 3 years of experience in AI and Generative AI. * Programming experience in Python ...

New

Berkley

Principal Engineer - AI Platform

Wilmington, DE · On-site

$131K - $175K/yr

Implement and maintain data pipelines, model deployment strategies, and monitoring systems. * Ensure high availability and reliability of AI services through effective troubleshooting and performance ...

Berkley

Principal Engineer - AI Platform

Wilmington, DE · On-site

$131K - $175K/yr

Implement and maintain data pipelines, model deployment strategies, and monitoring systems. * Ensure high availability and reliability of AI services through effective troubleshooting and performance ...

Berkley

Principal Engineer - AI Platform

Wilmington, DE · On-site

$131K - $175K/yr

Implement and maintain data pipelines, model deployment strategies, and monitoring systems. * Ensure high availability and reliability of AI services through effective troubleshooting and performance ...

Mwe

Senior Manager, AI & Analytics

Wilmington, DE

The Senior Manager, AI & Analytics owns the Accounting & Finance Systems Reporting, Data & AI ... Define and govern reporting standards, KPI definitions, and semantic models - driving data ...

DijavAI

AI Audit and Risk Assessment Lead

Dover, DE · On-site

$90 - $170/hr

Assess model performance and bias * Evaluate data quality and governance * Document findings and recommendations What We're Looking For * 9+ years in audit, risk management, or quality assurance

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Ai Model information

What is the difference between Ai Model vs Data Scientist?

AspectAi ModelData Scientist
Required CredentialsKnowledge of machine learning, programming skills, sometimes certifications in AI/MLDegree in data science, statistics, computer science; certifications beneficial
Work EnvironmentFocus on developing, training, and deploying AI modelsData analysis, interpretation, and visualization; often collaborates with AI teams
Industry UsageUsed in AI development, automation, and predictive modelingApplied across industries for insights, reporting, and decision-making

While both roles involve working with data and algorithms, an Ai Model primarily focuses on creating and refining AI systems, whereas a Data Scientist analyzes data to generate insights and supports AI development. The roles often overlap but serve distinct functions within the data and AI ecosystem.

What are some common challenges faced by professionals working as AI model developers, and how can they address them?

Professionals working as AI Model developers often encounter challenges such as managing large and complex datasets, ensuring model accuracy, and addressing issues of bias in algorithms. They may also need to balance the trade-off between model performance and interpretability, especially when deploying models in production environments. To overcome these challenges, AI Model developers typically collaborate closely with data engineers, domain experts, and other stakeholders, regularly validate their models, and stay updated with the latest advancements in the field to adopt best practices.

What is an AI model?

AI models are computer programs designed to simulate human intelligence by learning patterns from data and making predictions or decisions based on that learning. These models can perform a variety of tasks, such as recognizing speech, translating languages, analyzing images, and generating text. AI models are created using machine learning algorithms and are trained on large datasets to improve their accuracy and performance. Popular examples include neural networks, decision trees, and support vector machines. The effectiveness of an AI model depends on the quality of the data, the chosen algorithm, and the training process.

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

To excel as an AI Model Developer, you need strong programming skills (especially in Python), a solid understanding of machine learning algorithms, and typically a degree in computer science, data science, or a related field. Familiarity with ML frameworks like TensorFlow or PyTorch, cloud platforms, and relevant certifications such as TensorFlow Developer or AWS Machine Learning Specialty are valuable. Critical thinking, continuous learning, and effective collaboration with interdisciplinary teams are key soft skills for success. These competencies enable the creation of accurate, reliable AI models that can effectively solve complex real-world problems.

How to get into AI modeling?

To become an AI modeler, develop strong skills in programming languages like Python, learn machine learning frameworks such as TensorFlow or PyTorch, and gain experience with data preprocessing and model training. A background in computer science, mathematics, or related fields, along with relevant certifications or courses, can also improve your prospects.

What are popular job titles related to Ai Model jobs in Delaware?

For Ai Model jobs in Delaware, the most frequently searched job titles are:

What job categories do people searching Ai Model jobs in Delaware look for?

The top searched job categories for Ai Model jobs in Delaware are:

What cities in Delaware are hiring for Ai Model jobs?

Cities in Delaware with the most Ai Model job openings:

Ai Model jobs near you
Infographic showing various Ai Model job openings in Delaware as of August 2026, with employment types broken down into 2% Internship, 66% Full Time, 15% Part Time, and 17% Contract. Highlights an 78% In-person, and 22% Remote job distribution.

GenAI Engineer

ClifyX

Wilmington, DE • On-site

Full-time

Re-posted 29 days ago

Job description

Job Summary:
ClifyX is a company focused on innovative technology solutions, and they are seeking a GenAI Engineer to design and develop AI and Machine Learning solutions specifically for banking applications. The role involves building and deploying models, ensuring compliance, and collaborating with various teams to enhance AI capabilities.
Responsibilities:
• Design and develop AI/ML and Generative AI solutions for banking use cases including fraud detection, risk modeling, and customer analytics.
• Build, fine-tune, and deploy ML models and LLMs for credit scoring, AML, and automation
• Implement RAG-based GenAI applications using internal banking data
• Develop scalable data pipelines for training, validation, and real-time inference
• Collaborate with risk, compliance, finance, and business teams for AI solutions
• Ensure regulatory compliance and AI governance standards
• Implement data security, privacy, and access control mechanisms
• Integrate AI models into production using APIs and microservices
• Apply prompt engineering and model optimization techniques
• Monitor model performance, drift detection, and continuous improvement
• Develop explainable AI (XAI) for transparent decision-making
• Optimize cost, latency, and scalability of AI systems
• Troubleshoot AI/ML system issues across data and deployment layers
• Write efficient Python code using AI frameworks
• Follow MLOps best practices (CI/CD, automated deployment)
• Ensure responsible AI practices (bias, fairness, ethics)
• Mentor teams and contribute to enterprise AI platforms.
Qualifications:
Required:
• Design and develop AI/ML and Generative AI solutions for banking use cases including fraud detection, risk modeling, and customer analytics.
• Build, fine-tune, and deploy ML models and LLMs for credit scoring, AML, and automation
• Implement RAG-based GenAI applications using internal banking data
• Develop scalable data pipelines for training, validation, and real-time inference
• Collaborate with risk, compliance, finance, and business teams for AI solutions
• Ensure regulatory compliance and AI governance standards
• Implement data security, privacy, and access control mechanisms
• Integrate AI models into production using APIs and microservices
• Apply prompt engineering and model optimization techniques
• Monitor model performance, drift detection, and continuous improvement
• Develop explainable AI (XAI) for transparent decision-making
• Optimize cost, latency, and scalability of AI systems
• Troubleshoot AI/ML system issues across data and deployment layers
• Write efficient Python code using AI frameworks
• Follow MLOps best practices (CI/CD, automated deployment)
• Ensure responsible AI practices (bias, fairness, ethics)
• Mentor teams and contribute to enterprise AI platforms.
• Languages: Python
• AI/ML & GenAI: Machine Learning, Deep Learning, LLMs, Prompt Engineering, Fine-tuning
• Frameworks: TensorFlow, PyTorch
• GenAI Tools: LangChain, LlamaIndex
• Vector DB: Pinecone, FAISS
• Cloud Technologies: AWS / Azure / GCP
• Data Pipelines: ETL/ELT, Real-time & Batch Processing
• Integration: APIs, Microservices
• Concepts: RAG Architecture, XAI, Model Optimization
• Methodologies: Agile/Scrum, MLOps (CI/CD, Model Versioning, Deployment)
• Compliance: Banking regulations (SR 11-7, GDPR), Model Risk Management
• Soft Skills: Strong communication, stakeholder management, and analytical thinking
Company:
ClifyX provides innovative business solutions which satisfy requirements for mission-critical reliability, scalability, interoperations. Founded in 1998, the company is headquartered in South Plainfield, USA, with a team of 501-1000 employees. The company is currently Late Stage.
ClifyX logo

About ClifyX

Sourced by ZipRecruiter

ClifyX is a well-established player in the IT Services sector that specializes in providing result-oriented technological solutions to a wide range of industrial verticals. Based in South Plainfield, New Jersey, ClifyX offers a comprehensive selection of IT services that include project staffing, application development, professional consulting, and other IT-based solutions. While the company's website, clifyx.com, does not divulge the exact founding date, it is clear that ClifyX has grown into a renowned name within their domain, thanks to their unwavering commitment to innovative practices. The company's mission statement revolves around harnessing the power of technology to assist their clientele in steering their respective businesses towards success.

Industry

Recruiting and staffing services

Company size

51 - 200 Employees

Headquarters location

South Plainfield, NJ, US

Year founded

1998

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