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Machine Learning Engineer Jobs in New Jersey (NOW HIRING)

Purple Drive

Machine Learning Engineer

Newark, NJ

Machine Learning Engineer As a Machine Learning Engineer , you will play a critical role in designing, developing, and deploying advanced machine learning solutions that drive innovation and create ...

SageSure

Senior Machine Learning Engineer

Jersey City, NJ · On-site

$127K - $168K/yr

As a Senior Machine Learning Engineer, you'll play a crucial role in optimizing orchestration processes and ensuring fast and efficient model deployment and delivery. You'll work closely with ...

SageSure

Senior Machine Learning Engineer

Jersey City, NJ · On-site

$114K - $157K/yr

SageSure is a leader in catastrophe-exposed property insurance, seeking a Senior Machine Learning Engineer to optimize orchestration processes and ensure efficient model deployment. The role involves ...

SageSure

Senior Machine Learning Engineer

Jersey City, NJ · On-site

$127K - $168K/yr

As a Senior Machine Learning Engineer, you'll play a crucial role in optimizing orchestration processes and ensuring fast and efficient model deployment and delivery. You'll work closely with ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in New Jersey

Machine Learning Engineer information

See New Jersey salary details

$32K

$130.7K

$196.4K

How much do machine learning engineer jobs pay per year?

As of Jun 16, 2026, the average yearly pay for machine learning engineer in New Jersey is $130,731.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,000.00 and $157,400.00 per year, depending on experience, location, and employer.

Is ML full of coding?

Machine Learning Engineers typically do a significant amount of coding, especially in languages like Python or R, to develop algorithms, preprocess data, and build models. Strong programming skills are essential, along with knowledge of frameworks such as TensorFlow or PyTorch, but the role also involves data analysis, model evaluation, and collaboration with teams. Coding is a core component of the job, though some tasks may involve model deployment and optimization that require different skills.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or technology can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as they develop, implement, and maintain AI systems, requiring specialized skills in programming, data analysis, and model optimization. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and certain managerial positions—are also expected to persist despite AI advancements. These jobs typically require emotional intelligence, adaptability, and domain expertise that AI cannot easily replicate.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in New Jersey? The most popular types of Machine Learning Engineer jobs in New Jersey are:
What are popular job titles related to Machine Learning Engineer jobs in New Jersey? For Machine Learning Engineer jobs in New Jersey, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in New Jersey look for? The top searched job categories for Machine Learning Engineer jobs in New Jersey are:
What cities in New Jersey are hiring for Machine Learning Engineer jobs? Cities in New Jersey with the most Machine Learning Engineer job openings:
What are popular job titles related to Machine Learning Engineer jobs in NJ? For Machine Learning Engineer jobs in NJ, the most frequently searched job titles are:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in New Jersey as of June 2026, with employment types broken down into 98% Full Time, and 2% Part Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $130,731 per year, or $62.9 per hour.

Machine Learning Engineer

Purple Drive Technologies

Newark, NJ • On-site

Full-time

Retirement

Posted 16 days ago

Job description

Overview:
Role: Machine Learning Engineer
As a Machine Learning Engineer, you will play a critical role in designing, developing, and deploying advanced machine learning solutions that drive innovation and create measurable business value. You will collaborate closely with business stakeholders, data scientists, and cross-functional engineering teams to transform ideas into scalable, production-ready systems. This role requires both strong technical expertise and leadership ability to guide a small team and deliver impactful solutions.
Key Responsibilities
  • Lead and deliver machine learning projects from inception through production, building strong relationships with business partners and cross-functional teams.
  • Collaborate with business leaders and subject matter experts to define success criteria and optimize products, features, and models.
  • Partner with data scientists to design, implement, and train machine learning models.
  • Work with infrastructure teams to enhance architecture, scalability, stability, and performance of ML platforms.
  • Design and optimize data pipelines to support high-performance ML model training and inference.
  • Extend and customize machine learning libraries and frameworks for project-specific needs.
  • Define and implement model monitoring, governance, and operationalization processes for ML solutions.
  • Establish objectives and own the technical roadmap for ML platforms, ensuring delivery of results.
  • Define and promote standards of engineering and operational excellence for ML systems.
  • Apply architectural best practices in the delivery of data science and AI solutions.
Required Skills & Experience
  • Strong background in software engineering with proven experience as a Machine Learning Engineer.
  • Bachelor's degree in Computer Science, Computer Engineering, or related field; Master's preferred.
  • Advanced proficiency in Python, Java, and Scala with solid CS fundamentals (algorithms, data structures, multithreading).
  • Hands-on experience with Generative AI, LangChain, and RAG-based techniques.
  • Expertise in ML/DL libraries such as XGBoost, Scikit-learn, TensorFlow, and PyTorch.
  • Experience building and deploying ML solutions on public clouds (AWS, GCP).
  • Familiarity with ML platforms such as SageMaker, H2O, and DataRobot.
  • Strong knowledge of the ML lifecycle, including containerization, batch vs. real-time inference, and application security.
  • Proven track record in developing and deploying production-grade ML applications with cloud-based automation pipelines.
  • Experience working in Agile/Scrum environments with multiple stakeholders.
  • Excellent communication, collaboration, and problem-solving skills with thought leadership and innovative thinking.
Nice-to-Have
  • Experience with search platforms (e.g., Solr, Elasticsearch).
  • Hands-on experience building recommender systems.
  • Exposure to graph databases (e.g., Neo4j).
  • Familiarity with CI/CD tools (e.g., Jenkins).
  • Domain knowledge in Financial Services, Insurance, or 401K.
  • AWS Solutions Architect certification.

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