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

Newcode.ai

Head of Testing (AI)

New York, NY · On-site

Role Overview As Head of Testing, you will own the vision, strategy, and execution of product ... Experience evaluating LLM applications, AI agents, or generative AI workflows * Legal domain ...

Newcode.ai

Head of Testing (AI)

New York, NY

Role Overview As Head of Testing, you will own the vision, strategy, and execution of product ... Experience evaluating LLM applications, AI agents, or generative AI workflows * Legal domain ...

Newcode.ai

Head of Testing (AI)

New York, NY · On-site

Role Overview As Head of Testing, you will own the vision, strategy, and execution of product ... Experience evaluating LLM applications, AI agents, or generative AI workflows * Legal domain ...

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All JobsGenerative Ai Testing JobsGenerative Ai Testing Jobs in Edison, NJ

Generative Ai Testing information

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How much do generative ai testing jobs pay per hour?

As of Aug 17, 2026, the average hourly pay for generative ai testing in Edison, NJ is $55.62, according to ZipRecruiter salary data. Most workers in this role earn between $45.77 and $63.70 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 Edison, NJ?

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

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

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

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

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

Generative Ai Testing jobs near you
Infographic showing various Generative Ai Testing job openings in Edison, NJ as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 13% Part Time, 3% Temporary, 4% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $115,690 per year, or $55.6 per hour.

Applied AI and ML Lead - Generative AI

JPMorgan Chase & Co.

Jersey City, NJ • On-site

$171K - $260K/yr

Full-time

Medical, Retirement

Re-posted 2 days ago

JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 495 frontline employees who took The Breakroom Quiz

71st of 171 rated banks

Job description


Build what's next in enterprise AI-solutions that materially improve how teams make decisions, automate work, and serve internal customers. You will take generative AI from concept to production, help set the standard for semantic consistency across systems, and partner closely with stakeholders to turn complex business needs into measurable outcomes. You will mentor talent and influence technical direction across Corporate Technology and supported Corporate Functions.
As an Applied AI and Machine Learning Lead at JPMorganChase within Corporate Technology Data Science and AI, you will design, build, and deploy scalable analytical and generative AI solutions that deliver measurable business value. You will translate complex business needs into clear problem statements, success metrics, and production-ready models and intelligent workflows. You will help establish semantic modeling standards and a unified semantic layer that improves trust and consistency across analytics and AI use cases.
Job Responsibilities
  • Build generative AI, agentic AI, and large language model solutions in Python from proof of concept through production deployment with measurable outcomes
  • Design context engineering approaches to improve model accuracy, latency, reliability, and end-to-end user experience
  • Lead enterprise semantic modeling strategy, including ontology standards, governance practices, and lifecycle management
  • Partner with domain experts to create scalable ontologies that represent business entities, relationships, rules, and constraints
  • Define semantic integration patterns across data pipelines, application programming interfaces (APIs), data contracts, and experience layers to resolve semantic conflicts
  • Establish and govern a unified semantic layer that enables trusted analytics across business intelligence, machine learning, and transactional systems
  • Enable intelligent workflows and AI agents using ontology-driven context, semantic reasoning, and orchestration approaches
  • Build and maintain pipelines and frameworks for model training, evaluation, optimization, monitoring, and machine learning operations
  • Implement responsible AI practices, model risk controls, and governance aligned to regulated environments
  • Mentor engineers and data scientists, raising the bar on engineering rigor, reuse, and continuous improvement across the team

Required Qualifications, Capabilities, and Skills
  • Master's degree in a data science-related discipline and eight years of industry experience, or PhD in a data science-related discipline
  • Demonstrated experience developing and deploying machine learning and generative AI solutions using Python
  • Proven ability to write and maintain production-quality code, including documentation and maintainable design patterns
  • Experience building automated testing practices, including unit tests, and implementing continuous integration pipelines
  • Experience building and managing data pipelines and processing workflows for analytics and machine learning use cases
  • Strong scientific thinking and structured problem-solving skills, including hypothesis-driven analysis and metric definition
  • Strong written and verbal communication skills, with the ability to explain complex concepts to technical and non-technical stakeholders
  • Demonstrated ownership and attention to detail when operating in ambiguous, complex problem spaces
  • Ability to work independently while collaborating effectively across product, engineering, data, and business partners

Preferred Qualifications, Capabilities, and Skills
  • Experience designing or governing semantic models and ontologies, including taxonomy design and lifecycle governance
  • Experience implementing retrieval-augmented generation, tool use, and evaluation strategies for large language model applications
  • Familiarity with responsible AI techniques, including bias testing, explainability approaches, and model monitoring standards
  • Experience designing scalable architectures for real-time or near-real-time inference and intelligent workflow orchestration
  • Experience influencing cross-functional technical direction and mentoring engineers through design reviews and delivery execution

#LI-RB3
About Us
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
About the Team
Our Corporate Technology team relies on smart, driven people like you to develop applications and provide tech support for all our corporate functions across our network. Your efforts will touch lives all over the financial spectrum and across all our divisions: Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and within the Corporate Administrative Office. You'll be part of a team specifically built to meet and exceed our evolving technology needs, as well as our technology controls agenda.

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