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Deep Learning Developer Jobs in New Jersey (NOW HIRING)

Machine Learning Tutor

New Brunswick, NJ ยท Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Machine Learning Tutor

Clifton, NJ ยท Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Machine Learning Tutor

Paramus, NJ ยท Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Machine Learning Tutor

Westfield, NJ ยท Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Machine Learning Tutor

Jersey City, NJ ยท Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Machine Learning Tutor

Elizabeth, NJ ยท Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Machine Learning Tutor

Trenton, NJ ยท Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

Showing results 21-40

Deep Learning Developer information

What are the key skills and qualifications needed to thrive as a deep learning developer?

To thrive as a Deep Learning Developer, you need a strong background in computer science, mathematics, and proficiency in programming languages like Python, often supported by a degree in a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, and experience with cloud platforms or GPU acceleration, are commonly required technical skills. Analytical thinking, problem-solving abilities, and effective teamwork distinguish top performers in this role. These competencies are crucial for designing, training, and deploying advanced neural network models that address complex real-world problems.

What is a deep learning developer?

Deep Learning Developers are specialized software engineers or data scientists who design, build, and implement artificial intelligence systems using deep learning techniques. They work with neural networks, large datasets, and various frameworks like TensorFlow or PyTorch to develop models for tasks such as image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, optimization, and deployment to solve complex problems that require advanced pattern recognition. Deep Learning Developers often collaborate with AI researchers, data engineers, and product teams to integrate intelligent features into applications.

What is the difference between Deep Learning Developer vs Machine Learning Engineer?

AspectDeep Learning DeveloperMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, AI, or related; experience with neural networksBachelor's or Master's in CS, Data Science, or related; knowledge of algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on neural networksData-driven companies, software firms, industries applying machine learning
Industry UsagePrimarily in AI research, neural network development, deep learning projectsBroader application including predictive modeling, data analysis, and ML systems

Deep Learning Developers specialize in neural networks and deep learning models, often working on AI research and complex algorithms. Machine Learning Engineers have a broader focus on developing, deploying, and maintaining machine learning models across various applications. While both roles require similar educational backgrounds, their focus areas and industry applications differ.

What are some common challenges deep learning developers face when deploying models to production environments?

Deep Learning Developers often encounter challenges such as optimizing model performance for real-time inference, managing resource constraints (like GPU/CPU availability), and ensuring model reproducibility across different environments. Additionally, integrating deep learning models into existing software systems and maintaining them over time can be complex, especially as data and requirements evolve. Collaborating closely with DevOps, data engineers, and QA teams is essential to address these challenges and ensure smooth deployment and ongoing reliability.
Infographic showing various Deep Learning Developer job openings in New Jersey as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Lead, Machine Learning Engineer

Prudential Annuities Distributors (PAD)

Newark, NJ โ€ข On-site

$125 - $229.70/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 4 days ago


Job description

Job Classification: Technology - Data Analytics & Management

Are you interested in building capabilities that enable the organization with innovation, speed, agility, scalability and efficiency? The Global Technology team takes great pride in our culture where digital transformation is built into our DNA! When you join our organization at Prudential, youโ€™ll unlock an exciting and impactful career โ€“ all while growing your skills and advancing your profession at one of the worldโ€™s leading financial services institutions.

As a Lead, Machine Learning Engineer, you will partner with Data Scientists, Data Engineers, Data Analysts and other professionals to implement machine learning models that will deliver stability, producibility, scalability and integration with other products and services. You will implement capabilities to solve sophisticated business problems, deploy innovative products, services and experiences to delight our customers! In addition to advanced technical expertise and experience, you will bring excellent problem solving, communication and teamwork skills, along with agile ways of working, strong business insight, an inclusive leadership attitude and a continuous learning focus to all that you do.

Typical Day
  • Operationalize ML software models and components that solve realโ€‘world business problems, while working in collaboration with the Product and Data Science teams; remove complex technical impediments.
  • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
  • Leverage cloudโ€‘based architectures and technologies to deliver optimized ML models at scale.
  • Construct optimized data pipelines to feed ML models.
  • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
  • Bring a strong understanding of relevant and emerging technologies, provide input and coach team members and embed learning and innovation in the dayโ€‘toโ€‘day.
  • Work on complex problems in which analysis of situations or data requires an evaluation of intangible variables.
  • Use programming languages including but not limited to Python, R, SQL, Java or Scala, SQL.
Skills and Expertise
  • Bachelor of Computer Science or Engineering or experience in related fields.
  • Ability to coach others with minimal guidance and effectively leverage diverse ideas, experiences, thoughts and perspectives to the benefit of the organization.
  • Experience with agile development methodologies and Testโ€‘Driven Development (TDD).
  • Knowledge of business concepts, tools and processes that are needed for making sound decisions in the context of the companyโ€™s business.
  • Ability to learn new skills and knowledge on an onโ€‘going basis through selfโ€‘initiative and tackling challenges.
  • Excellent problem solving, communication and collaboration skills.
  • Advanced experience and/or expertise with several of the following:
    • Software Engineering & System Design: Requirement analysis, coding, and testing, version control, microservices architecture, building RestFul APIs, Distributed computing, architecture patterns, general understanding of computer architecture, Objectโ€‘oriented programming concepts.
    • Machine Learning and Deep Learning: Good understanding of ML algorithms like linear regression, logistic regression, etc., supervised, unsupervised, and reinforcement learning, AI Frameworks like TensorFlow, PyTorch, scikitโ€‘learn, Neural network, NLP, computer vision, and predictive analytics.
    • Model Performance Management: model monitoring, model validation, bias detection, explainability, performance, drift, outliers, etc.
    • Model Deployment: Thorough understanding of MDLC (Model Development Life Cycle), CI/CD/CT pipelines (using tools like Jenkins, CloudBees, Harness, etc.), A/B testing. Pipeline frameworks like MLFlow, AWS SageMaker pipeline, etc. model and data versioning.
    • Data Integration, Transformation & Processing: Transforming and mapping raw data to generate insights. Data wrangling through various tools. Understanding big data ecosystems, relational, NOSQL and graph databases, unstructured and semiโ€‘structured data. Data processing on distributed systems with Spark/PySpark.
    • Statistics and Computing: Strong knowledge of Linear Algebra, Probability and Statistics, Multivariate Calculus, Distributions like Poisson, Normal, Binomial, etc.
    • Programming Languages: Python, R, SQL, Java or Scala, SQL.
Compensation and Benefits

Prudential is required by state specific laws to include the salary range for this role when hiring a resident in applicable locations. The salary range for this role is from $125,000.00 to $229,700.00. Specific pricing for the role may vary within the above range based on many factors including geographic location, candidate experience, and skills. Market competitive base salaries, with a yearly bonus potential at every level.

  • Medical, dental, vision, life insurance, disability insurance.
  • Paid Time Off (PTO) and leave of absences, such as parental and military leave.
  • 401(k) plan with company match (up to 4%).
  • Companyโ€‘funded pension plan.
  • Wellness Programs including up to $1,600 a year for reimbursement of items purchased to support personal wellbeing needs.
  • Work/Life Resources to help support topics such as parenting, housing, senior care, finances, pets, legal matters, education, emotional and mental health, and career development.
  • Education Benefit to help finance traditional college enrollment toward obtaining an approved degree and many accredited certificate programs.
  • Employee Stock Purchase Plan: Shares can be purchased at 85% of the lower of two prices (Beginning or End of the purchase period), after one year of service.
  • Eligibility to participate in a discretionary annual incentive program is subject to the rules governing the program, whereby an award, if any, depends on various factors including, without limitation, individual and organizational performance.
Equal Opportunity

Prudential is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, sex, sexual orientation, gender identity, genetics, disability, marital status, age, veteran status, domestic partner status, medical condition or any other characteristic protected by law. If you need an accommodation to complete the application process, please email accommodations.hw@prudential.com. If you are experiencing a technical issue with your application or an assessment, please email careers.technicalsupport@prudential.com to request assistance.

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