AI ML Engineer Jobs in New Jersey
AI ML Engineer jobs in New Jersey are among the most active in the Northeast, with strong demand from pharma and life sciences, financial services, and enterprise technology firms at every level from entry-level through principal engineer. The largest hiring concentrations are in Jersey City, Princeton, and Parsippany, anchored by established employers like Johnson & Johnson, Cognizant, and Prudential Financial. The most in-demand specialties include natural language processing, computer vision, and ML platform engineering. Find a role that fits below and apply directly.
Find AI ML Engineer JobsOverview
Showing 5 of 15+ AI ML Engineer jobs
- Lead end-to-end generative AI and agentic AI initiatives from problem framing and experimentation through production release and measurable adoption.
- Design and evaluate foundation-model approaches, including model selection, fine-tuning strategies, retrieval and context design, and safety controls.
- Establish rigorous evaluation practices (quality, robustness, latency, cost, and risk) and translate results into clear recommendations and roadmaps.
- Build and operationalize production-grade machine learning and generative AI services using sound engineering practices, monitoring, and incident-ready controls.
- Define and drive semantic consistency across systems by leading semantic modeling standards and lifecycle governance in partnership with domain experts.
- Implement integration patterns that align data pipelines, application interfaces, and user experiences to reduce semantic conflicts and increase trust in outcomes.
- Partner with cross-functional leaders to define success metrics, manage trade-offs, and deliver outcomes aligned to business priorities and oversight expectations.
- Mentor and develop engineers and data scientists through technical leadership, reviews, and coaching to raise team capability and delivery velocity.
- Communicate complex technical concepts to both technical and non-technical audiences, influencing decisions through clarity, evidence, and pragmatism.
- Master's degree in computer science, engineering, statistics, or a related quantitative discipline.
- 7+ years of applied experience building and deploying machine learning and generative AI solutions in production environments.
- Strong proficiency in Python and modern machine learning frameworks (for example, PyTorch).
- Demonstrated ability to lead experimentation and evaluation, including defining metrics, running controlled comparisons, and documenting results for stakeholders.
- Experience deploying and operating models in production, including performance optimization, monitoring, and reliability trade-offs.
- Working knowledge of responsible AI practices, model risk concepts, and governance controls suitable for regulated environments.
- Strong software engineering fundamentals, including version control, code review, testing, and maintainable design.
- Proven ability to partner across product, engineering, and business stakeholders to translate ambiguous needs into clear outcomes and delivery plans.
- PhD in a relevant quantitative field or demonstrated applied research impact in machine learning or generative AI.
- Publications, patents, or open-source contributions that demonstrate research depth and practical impact.
- Hands-on experience with transformer-based architectures, large-scale training or fine-tuning, and GPU-enabled development workflows.
- Experience building agentic AI systems (tool use, orchestration, planning, and workflow automation) with strong evaluation discipline.
- Familiarity with semantic modeling, ontologies, or semantic-layer design to improve consistency across analytics and AI use cases.
- Experience applying AI solutions within financial services or other highly regulated industries.
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.
- Lead end-to-end generative AI and agentic AI initiatives from problem framing and experimentation through production release and measurable adoption.
- Design and evaluate foundation-model approaches, including model selection, fine-tuning strategies, retrieval and context design, and safety controls.
- Establish rigorous evaluation practices (quality, robustness, latency, cost, and risk) and translate results into clear recommendations and roadmaps.
- Build and operationalize production-grade machine learning and generative AI services using sound engineering practices, monitoring, and incident-ready controls.
- Define and drive semantic consistency across systems by leading semantic modeling standards and lifecycle governance in partnership with domain experts.
- Implement integration patterns that align data pipelines, application interfaces, and user experiences to reduce semantic conflicts and increase trust in outcomes.
- Partner with cross-functional leaders to define success metrics, manage trade-offs, and deliver outcomes aligned to business priorities and oversight expectations.
- Mentor and develop engineers and data scientists through technical leadership, reviews, and coaching to raise team capability and delivery velocity.
- Communicate complex technical concepts to both technical and non-technical audiences, influencing decisions through clarity, evidence, and pragmatism.
- Master's degree in computer science, engineering, statistics, or a related quantitative discipline.
- 7+ years of applied experience building and deploying machine learning and generative AI solutions in production environments.
- Strong proficiency in Python and modern machine learning frameworks (for example, PyTorch).
- Demonstrated ability to lead experimentation and evaluation, including defining metrics, running controlled comparisons, and documenting results for stakeholders.
- Experience deploying and operating models in production, including performance optimization, monitoring, and reliability trade-offs.
- Working knowledge of responsible AI practices, model risk concepts, and governance controls suitable for regulated environments.
- Strong software engineering fundamentals, including version control, code review, testing, and maintainable design.
- Proven ability to partner across product, engineering, and business stakeholders to translate ambiguous needs into clear outcomes and delivery plans.
- PhD in a relevant quantitative field or demonstrated applied research impact in machine learning or generative AI.
- Publications, patents, or open-source contributions that demonstrate research depth and practical impact.
- Hands-on experience with transformer-based architectures, large-scale training or fine-tuning, and GPU-enabled development workflows.
- Experience building agentic AI systems (tool use, orchestration, planning, and workflow automation) with strong evaluation discipline.
- Familiarity with semantic modeling, ontologies, or semantic-layer design to improve consistency across analytics and AI use cases.
- Experience applying AI solutions within financial services or other highly regulated industries.
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 15 AI ML Engineer Jobs in New Jersey
Find roles in New Jersey that match your experience and apply in just a few clicks.
Find AI ML Engineer JobsAI ML Engineer Jobs by City in New Jersey
Where New Jersey roles are concentrated, by current openings.
AI ML Engineer Job Market in New Jersey
A snapshot from current New Jersey openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Investment & Asset Management
- Fintech
- Food & Beverage
- Technology & Software
- Banking & Financial Services
What New Jersey Employers Look For
The qualifications that appear most often in AI ML engineer jobs across New Jersey.
- Bachelor's or master's degree in computer science, data science, or a closely related field
- Proficiency in Python and machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn
- Experience designing, training, and deploying machine learning models in production environments
- Familiarity with cloud platforms including AWS, Google Cloud, or Microsoft Azure for ML workloads
- Strong understanding of MLOps practices including model monitoring, versioning, and automated pipelines
- Experience with large-scale data processing tools such as Spark, Hadoop, or SQL-based data warehouses
AI ML Engineer Jobs in New Jersey: Frequently Asked Questions
How do you become a ai ml engineer in New Jersey?
Becoming an ai ml engineer in New Jersey typically starts with a bachelor's degree in computer science, mathematics, or a related quantitative field, with many roles preferring or requiring a master's. There is no state-issued license for this role in New Jersey. Employers focus on demonstrated skills in machine learning frameworks, cloud platforms, and production deployment, so building a portfolio of projects and earning cloud certifications from AWS, Google, or Microsoft strengthens your candidacy considerably.
Which companies hire ai ml engineers in New Jersey?
Employers hiring ai ml engineers in New Jersey right now include JPMorganChase, BNY, and 1Kosmos, based on current listings on Migrate Mate as of November 2026. New Jersey's dense concentration of pharmaceutical headquarters and financial services firms means demand is especially consistent for engineers who can apply ML to drug discovery pipelines, risk modeling, and fraud detection.
Which New Jersey cities have the most ai ml engineer jobs?
The cities with the most ai ml engineer openings in New Jersey are Jersey City, New Jersey, and Avenel. Jersey City's proximity to Manhattan draws financial technology and trading firms, Princeton's research corridor attracts pharma and biotech employers, and Parsippany serves as a hub for large enterprise technology and consulting operations that maintain significant New Jersey presences.
Are there remote ai ml engineer jobs in New Jersey?
Yes, and more than most fields. About 67% of ai ml engineer openings tied to New Jersey are remote or hybrid as of November 2026, reflecting how much of the work involves writing code, training models, and analyzing data rather than being on-site. The portions most likely to stay fully remote are model development and experimentation, while roles involving on-premises infrastructure or regulated data environments tend to require at least some in-office presence.
How can I get hired as a ai ml engineer in New Jersey with little or no experience?
The most realistic entry path is a strong portfolio of independent or academic ML projects paired with a relevant degree or cloud certification. Large New Jersey employers like Cognizant and Prudential Financial hire associate data scientists and junior ML engineers as entry points. Lateral moves from data analyst or software engineer roles are common. Contributing to open-source ML projects and earning an AWS or Google Cloud machine learning certification gives candidates a measurable edge when competing for first roles.
Where can I find and apply to ai ml engineer jobs in New Jersey?
You can find and apply to ai ml engineer jobs in New Jersey on Migrate Mate, which lists current New Jersey openings. Find roles that fit your background and apply directly to the ones that match.
See All 15 AI ML Engineer Jobs in New Jersey
Find roles in New Jersey that match your experience and apply in just a few clicks.
Find AI ML Engineer Jobs