Machine Learning Engineer Jobs in New Jersey
Machine Learning Engineer jobs in New Jersey are among the most active in the Northeast, with demand concentrated in financial services, pharmaceuticals, and enterprise technology and openings at every level from early-career through principal engineer. Most hiring is anchored in Jersey City, Newark, and Princeton, where firms like Johnson & Johnson, Prudential Financial, and Cognizant maintain substantial engineering operations. The most in-demand specialties are natural language processing, predictive modeling for financial risk, and MLOps infrastructure. Find a role that fits below and apply directly.
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Machine Learning Engineer – Recommendation Systems (Consumer Marketing)
We are seeking a skilled Machine Learning Engineer with deep expertise in building and optimizing recommendation systems within the consumer marketing space. The ideal candidate will have hands-on experience designing, implementing, and scaling personalized recommendation and targeting models that drive customer engagement, conversion, and revenue growth. Experience translating consumer behavior and marketing data into actionable, personalized experiences is essential.
Key Responsibilities:
- Design and develop machine learning models for recommendation and personalization systems (e.g., collaborative filtering, deep learning, hybrid approaches) tailored to consumer marketing use cases such as product recommendations, next-best-action, and audience targeting.
- Optimize models for scalability, performance, and real-time predictions across large-scale consumer datasets.
- Collaborate with business leaders, marketing partners, product and engineering teams to integrate models into production and campaign pipelines.
- Analyze and improve recommendation quality using metrics like precision, recall, click-through rate, conversion, and customer lifetime value.
- Leverage customer segmentation, behavioral, and first-party marketing data to enhance personalization and relevance.
- Experiment with cutting-edge techniques (e.g., reinforcement learning, graph neural networks, contextual bandits) to enhance recommendations and marketing outcomes.
Requirements
- 5+ years of experience in machine learning, with a focus on recommendation systems, ideally within consumer marketing, retail, e-commerce, or a related consumer-facing domain.
- Proven track record building personalization or recommendation models that measurably improved engagement or marketing performance.
- Proficiency in Python, TensorFlow, PyTorch, or similar ML frameworks.
- Strong understanding of algorithms like matrix factorization, neural networks, and ranking systems.
- Strong understanding of LTMs and agentic AI frameworks that can be customized for recommender systems.
- Experience working with consumer/marketing data, including behavioral, transactional, and campaign data (familiarity with CDPs, marketing analytics, or A/B testing is a plus).
- Experience with Databricks and AWS.
- Excellent problem-solving skills and a passion for delivering impactful, customer-centric solutions.
Machine Learning Engineer – Recommendation Systems (Consumer Marketing)
We are seeking a skilled Machine Learning Engineer with deep expertise in building and optimizing recommendation systems within the consumer marketing space. The ideal candidate will have hands-on experience designing, implementing, and scaling personalized recommendation and targeting models that drive customer engagement, conversion, and revenue growth. Experience translating consumer behavior and marketing data into actionable, personalized experiences is essential.
Key Responsibilities:
- Design and develop machine learning models for recommendation and personalization systems (e.g., collaborative filtering, deep learning, hybrid approaches) tailored to consumer marketing use cases such as product recommendations, next-best-action, and audience targeting.
- Optimize models for scalability, performance, and real-time predictions across large-scale consumer datasets.
- Collaborate with business leaders, marketing partners, product and engineering teams to integrate models into production and campaign pipelines.
- Analyze and improve recommendation quality using metrics like precision, recall, click-through rate, conversion, and customer lifetime value.
- Leverage customer segmentation, behavioral, and first-party marketing data to enhance personalization and relevance.
- Experiment with cutting-edge techniques (e.g., reinforcement learning, graph neural networks, contextual bandits) to enhance recommendations and marketing outcomes.
Requirements
- 5+ years of experience in machine learning, with a focus on recommendation systems, ideally within consumer marketing, retail, e-commerce, or a related consumer-facing domain.
- Proven track record building personalization or recommendation models that measurably improved engagement or marketing performance.
- Proficiency in Python, TensorFlow, PyTorch, or similar ML frameworks.
- Strong understanding of algorithms like matrix factorization, neural networks, and ranking systems.
- Strong understanding of LTMs and agentic AI frameworks that can be customized for recommender systems.
- Experience working with consumer/marketing data, including behavioral, transactional, and campaign data (familiarity with CDPs, marketing analytics, or A/B testing is a plus).
- Experience with Databricks and AWS.
- Excellent problem-solving skills and a passion for delivering impactful, customer-centric solutions.
See All 26 Machine Learning Engineer Jobs in New Jersey
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Find JobsMachine Learning Engineer Jobs by City in New Jersey
Where New Jersey roles are concentrated, by current openings.
Machine Learning Engineer Job Market in New Jersey
A snapshot from current New Jersey openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Fintech
- Banking & Financial Services
- Investment & Asset Management
- Technology & Software
- Insurance
What New Jersey Employers Look For
The qualifications that appear most often in machine learning engineer jobs across New Jersey.
- Bachelor's or master's degree in computer science, statistics, or a related quantitative field
- Proficiency in Python and machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn
- Experience designing and deploying machine learning models in production environments
- Familiarity with cloud platforms including AWS, Google Cloud, or Microsoft Azure
- Strong background in data preprocessing, feature engineering, and model evaluation methods
- Experience with MLOps practices including pipeline automation, model monitoring, and versioning
Machine Learning Engineer Jobs in New Jersey: Frequently Asked Questions
How do you become a machine learning engineer in New Jersey?
Machine learning engineering has no state-issued license in New Jersey, so the path runs through education and demonstrated technical skill. Most roles require at least a bachelor's degree in computer science, mathematics, or a closely related field, and a master's degree is increasingly expected at mid-level and above. New Jersey employers in pharma and finance place particular weight on hands-on project experience, a strong GitHub portfolio, and familiarity with industry-specific data workflows.
How much do machine learning engineers make in New Jersey?
Machine learning engineers in New Jersey earn a median of about $135,940 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $84,880 for the lowest 10% to over $207,200 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire machine learning engineers in New Jersey?
Employers hiring machine learning engineers in New Jersey right now include JPMorganChase, Versant, and ASRC Federal, based on current listings on Migrate Mate as of September 2026. New Jersey's concentration of pharmaceutical headquarters and financial services firms means many of these roles focus on drug discovery modeling, fraud detection, and risk analytics.
Which New Jersey cities have the most machine learning engineer jobs?
Jersey City, New Jersey, and Iselin have the most machine learning engineer openings in New Jersey. Jersey City and Newark attract financial services and enterprise tech roles tied to proximity to New York City, while Princeton draws heavily from the pharmaceutical and life sciences corridor anchored by companies headquartered along the Route 1 research belt.
Are there remote machine learning engineer jobs in New Jersey?
Yes, and more than most fields. About 45% of machine learning engineer openings tied to New Jersey are remote or hybrid as of September 2026, reflecting how much of the work involves writing code, training models, and analyzing data rather than on-site hardware or lab access. Research-heavy pharma roles are more likely to require some on-site presence, while fintech and enterprise software positions tend to offer the most flexibility.
How can I get hired as a machine learning engineer in New Jersey with little or no experience?
The most realistic entry path is through a data analyst or data engineer role at one of New Jersey's large pharma or financial services employers, then transitioning internally once you've built domain-specific modeling experience. Companies like Merck and Cognizant run rotational or associate programs that include applied analytics tracks. A portfolio of end-to-end projects, a master's degree from a New Jersey institution such as Rutgers or NJIT, and certifications in cloud ML platforms all strengthen a new-entrant's case.
Where can I find and apply to machine learning engineer jobs in New Jersey?
You can find and apply to machine learning engineer jobs in New Jersey on Migrate Mate, which lists current openings across the state. Find roles that fit your background and apply directly to the employers posting them.
See All 26 Machine Learning Engineer Jobs in New Jersey
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