AI ML Engineering Jobs in New Jersey
AI ML Engineering jobs in New Jersey are in strong demand, concentrated in pharmaceuticals, financial services, telecommunications, and defense contracting, with openings from entry-level data associate through principal engineer. Newark, Princeton, and Parsippany are the primary hiring corridors, anchored by employers such as Johnson & Johnson, Cognizant, and Verizon. The most sought-after specialties are natural language processing, MLOps infrastructure, and computer vision applied to drug discovery and fraud detection pipelines. Find a role that fits below and apply directly.
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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
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 professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
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
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 professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
See All 10 AI ML Engineering Jobs in New Jersey
Find roles in New Jersey that match your experience and apply in just a few clicks.
Find AI ML Engineering JobsAI ML Engineering Jobs by City in New Jersey
Where New Jersey roles are concentrated, by current openings.
AI ML Engineering Job Market in New Jersey
A snapshot from current New Jersey openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Fintech
- Food & Beverage
- Banking & Financial Services
- Investment & Asset Management
What New Jersey Employers Look For
The qualifications that appear most often in AI ML engineering jobs across New Jersey.
- Bachelor's or master's degree in computer science, statistics, or a closely related field
- Proficiency in Python and machine learning frameworks such as TensorFlow or PyTorch
- Experience designing, training, and deploying production-grade machine learning models
- Familiarity with cloud platforms including AWS, Google Cloud, or Microsoft Azure
- Ability to work with large-scale structured and unstructured datasets using SQL or Spark
- Strong communication skills for presenting model findings to non-technical stakeholders
AI ML Engineering Jobs in New Jersey: Frequently Asked Questions
How do you become a ai ml engineering in New Jersey?
The most direct path is a bachelor's degree in computer science, data science, or a related field followed by hands-on project experience in model building and deployment. New Jersey does not require a state-issued license for ai ml engineering roles. Employers across the state, particularly in the pharmaceutical corridor around Princeton and the financial services firms in Newark, consistently hire candidates who can demonstrate applied ML skills through a portfolio, internship, or prior industry work.
Which companies hire ai ml engineerings in New Jersey?
Employers hiring ai ml engineerings in New Jersey right now include JPMorganChase, Campbell's, and LMK Infotech, based on current listings on Migrate Mate as of November 2026. New Jersey's dense concentration of pharmaceutical headquarters and financial technology firms means hiring tends to cluster around applied research and production ML platforms rather than early-stage experimentation.
Which New Jersey cities have the most ai ml engineering jobs?
Jersey City, New Jersey, and Camden have the most ai ml engineering openings in New Jersey. Newark draws volume from financial services and telecommunications firms headquartered there, Princeton benefits from the pharmaceutical and biotech research corridor that runs through central New Jersey, and Parsippany attracts hiring from large enterprise technology and consulting offices established in Morris County.
Are there remote ai ml engineering jobs in New Jersey?
Yes, and more than most fields. About 33% of ai ml engineering openings tied to New Jersey are remote or hybrid as of November 2026, reflecting how much of the work involves coding, model training, and data analysis rather than on-site equipment. Roles focused on MLOps, data pipeline engineering, and research science tend to offer the most location flexibility.
How can I get hired as a ai ml engineering in New Jersey with little or no experience?
The most realistic entry path is through a machine learning or data engineering internship at one of New Jersey's large pharmaceutical or financial services employers, several of which run structured new-graduate programs. Johnson & Johnson's technology early-career programs and Cognizant's campus hiring in New Jersey both onboard candidates without prior full-time experience. Candidates who build a project portfolio demonstrating model deployment, even on open datasets, and who hold a relevant master's degree gain a clear edge for associate ML engineer or junior data scientist roles that can transition into full ai ml engineering positions.
Where can I find and apply to ai ml engineering jobs in New Jersey?
You can find and apply to ai ml engineering jobs in New Jersey on Migrate Mate, which lists current New Jersey openings across industries and experience levels. Search the available roles, identify the ones that fit your background, and apply directly through each listing.
See All 10 AI ML Engineering Jobs in New Jersey
Find roles in New Jersey that match your experience and apply in just a few clicks.
Find AI ML Engineering Jobs