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Machine Learning Remote Internship Jobs in Marlton, NJ

GATE 1 LTD

A.I. Manager

PA · On-site +1

Build and lead a remote AI team, including recruiting, mentoring, and performance management ... Guide model development, including machine learning, deep learning, NLP, and generative AI ...

YO AI Labs

SolidWorks Expert - Remote

Philadelphia, PA · Remote

$40 - $130/hr

Translate engineering requirements into structured CAD data suitable for AI learning and validation ... CNC machining. * Casting and forging. * Assembly modeling. * CAD editing and feature tree ...

Cisco

Senior Software Engineer (Remote)

Philadelphia, PA · Remote

$123K - $163K/yr

This is a remote role anywhere in the USA. Meet the Team Our software engineering team develops ... Familiarity with LLMs, AI agents, embeddings, or other machine-learning capabilities and their ...

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All JobsMachine Learning JobsMachine Learning Remote Internship JobsMachine Learning Remote Internship Jobs in Marlton, NJ

Machine Learning Remote Internship information

See Marlton, NJ salary details

$25.9K

$43.3K

$89.5K

How much do machine learning remote internship jobs pay per year?

As of Aug 23, 2026, the average yearly pay for machine learning remote internship in Marlton, NJ is $43,333.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,100.00 and $46,800.00 per year, depending on experience, location, and employer.

What is a machine learning remote internship?

A Machine Learning Remote Internship is a temporary, structured work experience where interns contribute to machine learning projects from a remote location, such as their home. Interns typically work with teams on tasks like data preprocessing, building models, and evaluating results, while gaining practical knowledge and mentoring. These internships are ideal for students or recent graduates looking to develop their skills in machine learning, programming, and data science without the need to relocate. They often involve working with Python, popular ML libraries, and real-world datasets. Communication and collaboration are maintained through online tools and regular meetings.

What types of projects can I expect to work on during a machine learning remote internship?

During a remote machine learning internship, you can expect to contribute to projects such as data preprocessing, model development, and performance evaluation. Interns often work on real-world datasets, applying techniques like regression, classification, clustering, or deep learning, depending on the organization's focus. Collaboration with data scientists, engineers, and other interns is common, typically via virtual meetings and shared code repositories. These projects provide hands-on experience and often culminate in presenting your findings to the team, offering valuable exposure to industry-standard workflows and tools.

What are the key skills and qualifications needed to thrive as a machine learning remote intern, and why are they important?

To thrive as a Machine Learning Remote Intern, you need a solid background in programming (especially Python), mathematics/statistics, and a foundational understanding of machine learning concepts, often gained through coursework or relevant projects. Familiarity with machine learning libraries (like TensorFlow, PyTorch, and scikit-learn), version control systems (such as Git), and cloud platforms is typically expected. Strong problem-solving abilities, self-motivation, and effective remote communication set top interns apart. These skills and qualities enable efficient collaboration, successful project delivery, and continuous learning in a dynamic, distributed work environment.

What is the difference between Machine Learning Remote Internship vs Data Science Intern?

AspectMachine Learning Remote InternshipData Science Intern
Required CredentialsBasic programming, math, and machine learning knowledgeStatistics, programming, and data analysis skills
Work EnvironmentRemote, collaborative teams, project-basedRemote or on-site, data analysis and modeling tasks
Industry UsageTech, AI, startups, research labsTech, finance, healthcare, consulting
Search & Comparison IntentUnderstanding internship roles in MLExploring data science internship opportunities

Machine Learning Remote Internships focus on developing models and algorithms, often requiring knowledge of programming and math. Data Science Internships involve analyzing data, creating reports, and supporting decision-making. While both roles are remote and industry-relevant, ML internships emphasize algorithm development, whereas data science roles focus on data analysis and visualization.

What job categories do people searching Machine Learning Remote Internship jobs in Marlton, NJ look for?

The top searched job categories for Machine Learning Remote Internship jobs in Marlton, NJ are:

What cities near Marlton, NJ are hiring for Machine Learning Remote Internship jobs?

Cities near Marlton, NJ with the most Machine Learning Remote Internship job openings:

Machine Learning Remote Internship jobs near you

A.I. Manager

GATE 1 LTD

PA • On-site, Remote

Other

Re-posted 9 days ago

Job description

About the Company
We are a forward-thinking company committed to leveraging innovation to drive business growth and operational excellence. As part of our continued investment in technology, we are building an in-house AI department to lead the design, development, and deployment of AI-driven solutions across key areas of our business.
Why Join Us
  • Be a founding leader in shaping our AI capabilities and strategy.
  • Work remotely with flexibility and autonomy.
  • Join a collaborative, innovative, and mission-driven team.
  • Competitive compensation, benefits, and growth opportunities.

Job Summary
We are seeking an experienced and visionary AI Manager to lead the formation and development of our in-house AI team. This is a foundational leadership role responsible for designing the AI strategy, building a high-performing team, and overseeing the delivery of impactful AI solutions that align with our business objectives. You will work cross-functionally with business stakeholders, engineers, analysts, and product managers to identify opportunities where AI can create value, and then lead the implementation of those solutions from concept to production.
Key Responsibilities
Strategy & Leadership
  • Define and execute the AI roadmap in alignment with business goals.
  • Serve as the company's internal expert on AI trends, opportunities, and risks.
  • Build and lead a remote AI team, including recruiting, mentoring, and performance management.
  • Collaborate with leadership to identify high-impact AI use cases across departments.

Project Management & Delivery
  • Oversee the development and deployment of AI models and tools.
  • Ensure AI projects are delivered on time, within scope, and meet quality standards.
  • Drive adoption of best practices in data science, MLOps, and model governance.

Technical Oversight
  • Guide model development, including machine learning, deep learning, NLP, and generative AI, depending on use cases.
  • Ensure scalable and maintainable AI systems and pipelines.
  • Partner with data engineering teams to ensure data quality, availability, and security.

Cross-Functional Collaboration
  • Communicate complex AI concepts clearly to non-technical stakeholders.
  • Translate business problems into data-driven solutions.
  • Advocate for ethical AI practices and responsible data use across the organization.

Required
  • Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
  • 5+ years of experience in applied AI, machine learning, or data science roles.
  • 2+ years of experience in a leadership or managerial capacity.
  • Proven experience delivering AI/ML solutions in a business environment.
  • Proficiency in Python and common ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
  • Strong understanding of cloud platforms (e.g., AWS, Azure, GCP) and MLOps tools.
  • Experience working in agile, cross-functional teams.

Preferred
  • Experience in building and scaling internal AI functions from the ground up.
  • Familiarity with LLMs, generative AI, and prompt engineering.
  • Exposure to AI use cases across multiple domains (e.g., marketing, operations, customer support).
  • Excellent communication, presentation, and stakeholder management skills.

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