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Machine Learning Developer Intern Jobs in Riverton, NJ

Senior Machine Learning Engineer

Malvern, PA · On-site

$102K - $140K/yr

Design, build, and maintain end-to-end machine learning pipelines from research through production deployment. * Engineer scalable training, inference, and retraining workflows using AWS SageMaker.

We are currently seeking a Senior Machine Learning Engineer to join our team in Moorestown, NJ. Responsibilities: * Develops, researches, and applies machine learning, deep learning, visual ...

Senior Machine Learning Engineer

Moorestown, NJ · On-site

$103K - $141K/yr

We are currently seeking a Senior Machine Learning Engineer to join our team in Moorestown, NJ. Responsibilities: * Develops, researches, and applies machine learning, deep learning, visual ...

Senior Machine Learning Engineer

Moorestown, NJ · On-site

$103K - $141K/yr

We are currently seeking a Senior Machine Learning Engineer to join our team in Moorestown, NJ. Responsibilities: * Develops, researches, and applies machine learning, deep learning, visual ...

Showing results 21-40

Machine Learning Developer Intern information

See Riverton, NJ salary details

$24.4K

$40.8K

$84.2K

How much do machine learning developer intern jobs pay per year?

As of Sep 11, 2026, the average yearly pay for machine learning developer intern in Riverton, NJ is $40,761.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,100.00 and $44,000.00 per year, depending on experience, location, and employer.

What does a machine learning developer intern do?

A Machine Learning Developer Intern assists with developing, testing, and implementing machine learning models and algorithms under the guidance of experienced engineers or data scientists. Their tasks may include data preprocessing, model training, evaluating model performance, and helping deploy models into production environments. Interns often collaborate with team members to solve real-world problems using machine learning techniques and may also assist in researching new methodologies or optimizing existing solutions. This role provides hands-on experience in coding, data analysis, and applying theoretical concepts to practical scenarios.

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

To thrive as a Machine Learning Developer Intern, you need a solid understanding of programming (especially Python), statistics, and machine learning concepts, often supported by coursework or relevant project experience. Familiarity with ML frameworks like TensorFlow or PyTorch, and tools such as Jupyter Notebooks and version control systems like Git, is typically expected. Strong analytical thinking, eagerness to learn, and effective communication help interns contribute to team projects and adapt quickly. These skills are essential for solving real-world problems, collaborating with teams, and building a foundation for a successful career in machine learning.

How do machine learning developer interns typically collaborate with data scientists and engineers during their internship?

Machine Learning Developer Interns often work closely with data scientists to understand the problem domain, gather relevant datasets, and select appropriate models. They also collaborate with software engineers to integrate machine learning solutions into existing systems, ensuring scalability and performance. Regular communication through stand-up meetings, code reviews, and collaborative platforms is common, allowing interns to learn best practices and receive feedback on their work. This teamwork not only enhances technical skills but also provides valuable exposure to real-world deployment and project lifecycle management.

What is the difference between Machine Learning Developer Intern vs Data Scientist Intern?

AspectMachine Learning Developer InternData Scientist Intern
Required CredentialsTypically pursuing or recently completed a degree in Computer Science, Data Science, or related fields; knowledge of programming languages like Python or JavaSimilar educational background; strong skills in statistics, programming, and data analysis
Work EnvironmentHands-on experience with ML models, algorithms, and software development in tech or research settingsData analysis, visualization, and interpretation in business or research contexts
Employer & Industry UsageTech companies, startups, research labs focusing on AI/ML projectsBusiness, finance, healthcare, and research organizations analyzing large datasets

Both roles involve working with data and programming, but Machine Learning Developer Interns focus more on building and deploying ML models, while Data Scientist Interns emphasize data analysis and insights. The roles often overlap, especially in tech environments, but their core tasks differ slightly.

What cities near Riverton, NJ are hiring for Machine Learning Developer Intern jobs?

Cities near Riverton, NJ with the most Machine Learning Developer Intern job openings:

Principal Machine Learning Engineer[W2 ROLE]

Philadelphia, PA • On-site

SmartIPlace
IT Services • 51 - 200 employees

Contractor

Re-posted 27 days ago


Job description

Title: Principal Machine Learning Engineer

Location: Philadelphia, PA (Hybrid – Onsite Tuesdays & Wednesdays)
Duration: 6+ Months Contract-to-Hire
Employment Type: W2
Work Authorization: Must be authorized to work in the U.S.

Job Summary

Medical Guardian is seeking a Principal Machine Learning Engineer to lead the design, development, deployment, and optimization of machine learning solutions supporting predictive analytics, scoring, decision intelligence, and AI-driven automation. This is a hands-on technical leadership role focused on building production-ready ML models while partnering with stakeholders to solve complex business problems.

Key Responsibilities
  • Design, build, validate, and deploy machine learning models for prediction, scoring, risk detection, prioritization, and decision support.
  • Perform exploratory data analysis (EDA), feature engineering, model training, tuning, validation, and performance evaluation.
  • Develop scalable ML pipelines using Python, SQL, Spark, Databricks, MLflow, scikit-learn, XGBoost, and similar technologies.
  • Build reusable feature engineering frameworks and model-ready datasets.
  • Monitor production models for performance, drift, calibration, retraining, and lifecycle management.
  • Collaborate with business and technical stakeholders to translate business challenges into ML solutions.
  • Ensure models are explainable, maintainable, and production-ready.
  • Follow software engineering best practices including version control, testing, documentation, and code quality.
  • Provide technical leadership and guidance on AI/ML best practices and model design.
Required Qualifications
  • 5+ years of hands-on experience in machine learning model development.
  • 3+ years of experience deploying and supporting machine learning models in production environments.
  • Strong programming experience with Python and SQL.
  • Experience with Databricks, Apache Spark, MLflow, Snowflake, Azure, AWS, or similar cloud/data platforms.
  • Strong understanding of feature engineering, model evaluation, model monitoring, drift detection, calibration, thresholding, and retraining.
  • Experience developing predictive models, scorecards, and decision-support systems.
  • Ability to communicate technical concepts effectively to both technical and non-technical stakeholders.
  • Strong software engineering practices including testing, documentation, reproducibility, and maintainable code.
Preferred Qualifications
  • Experience with Generative AI and AI automation.
  • Knowledge of MLOps and production machine learning lifecycle management.
  • Experience with explainable AI (XAI) and transparent modeling techniques.
  • Background in predictive analytics, customer engagement, or risk modeling.
  • Experience working in Agile environments.
Required Skills
  • Machine Learning
  • Python
  • SQL
  • Databricks
  • Apache Spark
  • MLflow
  • scikit-learn
  • XGBoost
  • Snowflake
  • Azure / AWS
  • Feature Engineering
  • Predictive Modeling
  • Model Deployment
  • MLOps
  • Generative AI
  • AI Automation
  • Model Monitoring
  • Stakeholder Management

Smart-iPlace logo

About Smart-iPlace

Sourced by ZipRecruiter

SMART-iPLACE provides innovative staffing and consulting solutions that help our clients achieve their business objectives. We can understand and support all areas of your IT systems from back-end infrastructure to front-end personal productivity. Our goal is create innovative IT solutions that enable your business to be more agile and competitive.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Irving, TX, US

Year founded

2021

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