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Generative Ai Testing Jobs in Riverside, NJ (NOW HIRING)

HCL Global Systems Inc

AI/ML Engineer

Malvern, PA · On-site

They are seeking an AI/ML Engineer to implement agentic frameworks, develop generative AI ... testing, version control (e.g., Git), and security. • Familiarity with the Machine Learning ...

Campbell's

Data Engineer, DA&AI Co-Op

Camden, NJ · On-site

$115K - $138K/yr

Prototype AI Agents: Assist in building and testing AI agents designed to automate internal ... Hands-on training in Generative AI and Agentic technologies. * Mentorship from senior AI Engineers ...

Campbell's

Data Engineer, DA&AI Co-Op

Camden, NJ · On-site

$115K - $138K/yr

Prototype AI Agents: Assist in building and testing AI agents designed to automate internal ... Hands-on training in Generative AI and Agentic technologies. * Mentorship from senior AI Engineers ...

Campbell Soup Company

Data Engineer, DA&AI Co-Op

Camden, NJ · On-site

$115K - $138K/yr

Prototype AI Agents: Assist in building and testing AI agents designed to automate internal ... Hands-on training in Generative AI and Agentictechnologies. * Mentorship from senior AI Engineers ...

Campbell Soup Company

Data Engineer, DA&AI Co-Op

Camden, NJ · On-site

$115K - $138K/yr

Prototype AI Agents: Assist in building and testing AI agents designed to automate internal ... Hands-on training in Generative AI and Agentictechnologies. * Mentorship from senior AI Engineers ...

Campbell Soup Company

Data Engineer, DA&AI Co-Op

Camden, NJ · On-site

$115K - $138K/yr

Prototype AI Agents: Assist in building and testing AI agents designed to automate internal ... Hands-on training in Generative AI and Agentictechnologies. * Mentorship from senior AI Engineers ...

Campbell's

Data Engineer, DA&AI Co-Op

Camden, NJ · On-site

$115K - $138K/yr

Prototype AI Agents: Assist in building and testing AI agents designed to automate internal ... Hands-on training in Generative AI and Agentic technologies. * Mentorship from senior AI Engineers ...

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Generative Ai Testing information

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How much do generative ai testing jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for generative ai testing in Riverside, NJ is $54.26, according to ZipRecruiter salary data. Most workers in this role earn between $44.66 and $62.16 per hour, depending on experience, location, and employer.

What is generative AI testing?

Generative AI Testing refers to the process of evaluating and validating AI systems, particularly those that generate content such as text, images, or code. This type of testing focuses on assessing the accuracy, reliability, fairness, and safety of generative models to ensure they function as intended and avoid producing harmful or biased outputs. Testers use various methods, including automated and manual techniques, to check for issues like hallucinations, inappropriate content, or security vulnerabilities. The goal is to build trust in generative AI systems and ensure they meet quality and ethical standards before deployment.

What are some common challenges faced when testing generative AI models, and how can I prepare to address them in this role?

Testing generative AI models often involves unique challenges such as evaluating the quality and relevance of generated content, detecting bias or inappropriate outputs, and ensuring model consistency across various prompts. You may work closely with data scientists and engineers to create robust evaluation frameworks and develop automated as well as manual testing strategies. Familiarity with prompt engineering, statistical evaluation techniques, and domain-specific knowledge will help you address these challenges effectively. Proactively staying updated on industry best practices and collaborating with cross-functional teams are key to success in this dynamic field.

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

To thrive as a Generative AI Testing Specialist, you need a robust understanding of machine learning principles, model evaluation techniques, and a background in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and model evaluation frameworks, as well as experience with automated testing platforms, is typically required. Analytical thinking, attention to detail, and strong communication skills help you identify model weaknesses and collaborate effectively with development teams. These skills are crucial to ensure the reliability, safety, and ethical deployment of generative AI solutions.

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

AspectGenerative Ai TestingData Scientist
Required CredentialsKnowledge of AI models, testing tools, programming skillsStatistics, programming, data analysis certifications
Work EnvironmentAI development teams, testing labs, tech companiesResearch labs, tech firms, finance, healthcare
Employer & Industry UsageAI product testing, quality assurance in techData analysis, predictive modeling across industries

Generative Ai Testing focuses on evaluating and validating AI-generated content and models, ensuring quality and accuracy. Data Scientists analyze data, build models, and derive insights. While both roles require programming and AI knowledge, Generative Ai Testing emphasizes testing processes, whereas Data Scientists focus on data analysis and model development.

How do I become a Generative AI Testing?

To become a Generative AI Tester, develop skills in machine learning, natural language processing, and programming languages like Python. Gain experience with AI frameworks such as TensorFlow or PyTorch and understand data quality and model evaluation techniques. Relevant certifications and hands-on projects can enhance your qualifications for roles in AI testing environments.

Is Generative AI Testing a good career?

Generative AI Testing is a growing field within AI development, focusing on evaluating the quality and safety of AI-generated content. It requires skills in machine learning, programming, and understanding AI models, often involving tools like Python and TensorFlow. The role offers opportunities in tech companies and research labs, with demand expected to increase as AI applications expand.

What are popular job titles related to Generative Ai Testing jobs in Riverside, NJ?

For Generative Ai Testing jobs in Riverside, NJ, the most frequently searched job titles are:

What job categories do people searching Generative Ai Testing jobs in Riverside, NJ look for?

The top searched job categories for Generative Ai Testing jobs in Riverside, NJ are:

What cities near Riverside, NJ are hiring for Generative Ai Testing jobs?

Cities near Riverside, NJ with the most Generative Ai Testing job openings:

Generative Ai Testing jobs near you

AI/ML Integration Specialist - ACWS

Fort Dix, NJ

Data Systems Analysts, Inc.
201 - 500 employees
Learn more about Data Systems Analysts, Inc.external

Full-time

Posted 21 days ago

Job description

AI/ML Integration Specialist Summary: Lead AI/ML integration by delivering practical, secure, and governed capabilities that improve productivity, automation, search, analytics, and decision support while ensuring proposed AI/ML solutions are authorized, usable in Army environments, aligned with mission and compliance requirements, and implemented without disrupting operations.

Required Skills: 

  • Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Engineering, Information Systems, or a related technical field. 
  • AWS Certified Machine Learning Engineer, AWS Certified Generative AI Developer or AI/ML equivalent certification and Comp Tia Sec+
  • Active Secret Clearance
  • 6+ years of experience supporting AI/ML, data science, analytics, intelligent automation, software integration, or enterprise application modernization. 
  • Experience designing and integrating AI/ML capabilities into enterprise applications, workflows, APIs, data services, reporting tools, or user-facing systems. 
  • Working knowledge of machine learning, natural language processing, generative AI, prompt engineering, model evaluation, data pipelines, and responsible AI practices. 
  • Experience with Python, SQL, APIs, cloud services, structured and unstructured data, and integration patterns used to connect AI/ML capabilities with operational systems. 
  • Ability to translate mission needs, user pain points, and business requirements into practical AI/ML use cases, prototypes, implementation plans, and measurable outcomes. 
  • Knowledge of secure software delivery, data protection, privacy, model governance, human-in-the-loop controls, and compliance considerations for federal or regulated environments. 
  • Strong collaboration skills with the ability to work across architecture, development, data, cybersecurity, DevSecOps, testing, product, and government stakeholder teams. 
  • Active Secret Clearance

Desired Qualifications: 

  • Experience identifying and implementing AI/ML use cases for federal acquisition, contracting, financial, procurement, or mission workflow systems
  • Experience with AI-enabled acquisition capabilities such as document analysis, clause/compliance assistance, contextual help, search, summarization, anomaly detection, workload assignment, recommendation engines, reporting, and decision support.
  • Experience integrating AI/ML capabilities with Appian, LC/NC platforms, Java services, APIs, databases, business intelligence tools, or cloud-hosted environments. 
  • Experience developing AI-enabled search, document analysis, workflow automation, anomaly detection, recommendation, summarization, reporting, or decision-support capabilities. 

Responsibilities: 

  • Lead identification, design, and integration of AI/ML use cases that improve ACWS modernization, user efficiency, workflow automation, analytics, and decision support. 
  • Translate operational needs and stakeholder requirements into AI/ML solution concepts, technical requirements, prototypes, backlog items, and implementation guidance. 
  • Partner with architects, data administrators, developers, DevSecOps, cybersecurity, testers, and functional analysts to integrate AI/ML capabilities into secure enterprise delivery. 
  • Support AI/ML model selection, data preparation, prompt design, integration patterns, validation planning, and performance monitoring. 
  • AI-enabled delivery, testing, validation, and release support.
  • Implement responsible AI practices, including human review, explainability considerations, data protection, access control, auditability, and appropriate governance. 
  • Coordinate testing and validation of AI/ML-enabled capabilities to ensure accuracy, reliability, security, usability, and alignment with mission outcomes. 
  • Maintain AI/ML documentation, design assumptions, use case traceability, model/integration decisions, risks, and implementation recommendations. 
  • Evaluate emerging AI/ML technologies and recommend practical improvements that support ACWS modernization without disrupting operational continuity. 

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