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Machine Learning Engineer Jobs in Cherry Hill, NJ

RIT Solutions, Inc.

Data Engineer

Malvern, PA · On-site

$112K - $134K/yr

Responsibilities : • We are seeking an experienced Machine Learning Engineer to join our AI/ML Engineering team. You will be responsible for developing and optimizing complex data pipelines ...

Varsity Tutors

Machine Learning Tutor

Chester, PA · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Elsevier

Senior ML Ops Engineer

Philadelphia, PA · On-site

$99K - $137K/yr

In this role, the Senior Machine Learning Engineer will bridge Data Science and Engineering to develop AI-based features and ensure the deployment of secure, reliable, and scalable machine learning ...

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Showing results 21-40

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Cherry Hill, NJ

Machine Learning Engineer information

See Cherry Hill, NJ salary details

$31.1K

$127.3K

$191.3K

How much do machine learning engineer jobs pay per year?

As of Aug 10, 2026, the average yearly pay for machine learning engineer in Cherry Hill, NJ is $127,316.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,400.00 and $153,300.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

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.

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 cities near Cherry Hill, NJ are hiring for Machine Learning Engineer jobs? Cities near Cherry Hill, NJ with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Cherry Hill, NJ as of August 2026, with employment types broken down into 78% Full Time, and 22% Contract. Highlights an 100% In-person job distribution, with an average salary of $127,316 per year, or $61.2 per hour.

Principal Data Platform & Machine Learning Engineer

BE Group

Malvern, PA • On-site

$132K - $177K/yr

Full-time

Posted 13 days ago

Job description

We are assisting our client in hiring for a Principal Data Platform & Machine Learning Engineer.

Our client is an established SaaS company serving banks, credit unions, and fintechs. Their cloud-based platform helps financial institutions improve collections performance, deliver a better consumer experience, reduce operating costs, anticipate delinquencies, and make more informed credit decisions.

This is a hybrid position based in Malvern, Pennsylvania. Candidates should be local to the Greater Philadelphia region and able to work onsite several days each week.

As part of a significant investment in Data & AI, our client is expanding its engineering organization with two newly created Machine Learning positions. This role will define the technical foundation that powers the company's next generation of predictive analytics and AI capabilities.

This is a highly hands-on Principal Engineering opportunity for someone who enjoys building platforms as much as building software. You'll establish the architecture, data pipelines, APIs, engineering standards, and machine learning infrastructure that enable intelligent products to scale across the business.

You'll work closely with Product, Engineering, and executive leadership while mentoring other engineers and helping shape the technical direction of the platform. This is an opportunity to influence architecture, modernize engineering practices, and build production AI capabilities that directly impact customers and the future of the business.

What We're Looking For
  • Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical discipline.
  • 7+ years of experience building large-scale data platforms, cloud-native applications, or production machine learning systems.
  • Strong Python and SQL development skills.
  • Experience designing scalable data architectures, APIs, distributed data processing solutions, and machine learning platforms.
  • Experience with Azure, Databricks, MLflow, CI/CD, infrastructure automation, and MLOps.
  • Proven ability to establish engineering standards, technical direction, and software best practices while remaining highly hands-on.
  • Experience mentoring engineers and collaborating across multiple technical disciplines.
Preferred Experience
  • Financial services, banking, lending, collections, credit risk, or fintech.
  • Designing enterprise-scale data platforms and machine learning infrastructure.
  • Building highly available, cloud-native SaaS applications.
  • AI-assisted software development tools and modern engineering practices.
  • Passion for solving complex technical challenges while helping other engineers succeed.