2

Machine Learning Intern Remote Jobs in North Carolina

$110K - $140K/yr

Machine Learning EngineerFull-time We are expanding rapidly and are seeking new, experienced and hands-on team members who think outside of the box (and are not afraid to share their thoughts), will ...

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Machine Learning Intern Remote information

What does a machine learning intern do when working remotely?

A remote Machine Learning Intern typically assists with data collection, cleaning, and analysis, helps develop and test machine learning models, and collaborates with team members through virtual meetings and code repositories. They may also research new algorithms, document their work, and present findings to their supervisors. The role provides hands-on experience in applying machine learning concepts to real-world problems while working from a remote location.

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

To thrive as a Machine Learning Intern (Remote), a solid understanding of programming (especially Python), statistics, and foundational machine learning concepts—often supported by coursework or a relevant degree—is essential. Familiarity with tools like TensorFlow, PyTorch, Jupyter Notebooks, and version control systems (e.g., Git) is typically required, along with experience using data analysis libraries. Strong problem-solving skills, initiative, and clear communication are valuable soft skills for collaborating virtually and adapting to remote work environments. These skills and qualities enable effective contribution to projects, smooth team communication, and successful learning in a dynamic, distributed setting.

What types of projects can I expect to work on as a machine learning intern?

As a remote Machine Learning Intern, you can typically expect to contribute to projects such as data preprocessing, building and evaluating machine learning models, and assisting with the deployment of models into production environments. You may also help with tasks like feature engineering, exploratory data analysis, and preparing technical documentation. Collaboration is usually done through virtual meetings and code repositories, and you'll often work closely with data scientists, engineers, and mentors who provide guidance and feedback. This hands-on experience helps you gain exposure to industry-standard tools and workflows, preparing you for more advanced roles in the future.

What are the most commonly searched types of Machine Learning Remote jobs in North Carolina?

The most popular types of Machine Learning Remote jobs in North Carolina are:

What cities in North Carolina are hiring for Machine Learning Intern Remote jobs?

Cities in North Carolina with the most Machine Learning Intern Remote job openings:

Business Analytics- Intern (Remote)

DivIHN

Charlotte, NC • On-site, Remote

Contractor

Posted 7 days ago


Job description

For further inquiries about this opportunity, please contact one of our Talent Specialists, Tenishbabu at 224 507 1292 or Anto at 2243692969.
Title: Business Analytics- Intern (Remote)
Duration: 9 Months
Location: Charlotte, NC

Prefered candidates in EST, CST Time Zone
Only W2 candidates are eligible for this position. Third-party or C2C candidates will not be considered.
Description
This role will be responsible for leading detailed research and analysis on assigned competitive intelligence topics in support of business strategy and planning activities. Analytics will also be applied internally to evaluate select business opportunities. Time will flex between ongoing analyst activities and project-based assignments.
Key Skills and Competencies
  • Advanced Analytics: Use data-driven approaches, statistical modeling, and machine learning tools to extract insights and inform decision-making.
  • Automation Expertise: Identify and implement process automation solutions to improve efficiency and scalability.
  • Business Acumen: Understand market dynamics, competitive positioning, and customer needs.
  • Strategic Thinking: Identify strategic issues, analyze research and data, consider implications, and make actionable recommendations.
  • Innovation Management: Collaborate on automation-driven innovation processes for product enhancements or process improvements.
  • Communication: Present updates, recommendations, and findings to senior leadership with clarity and precision.

Structure
1. Strategy & Planning: Developing strategies to address business challenges and long-term opportunities using analytics-driven insights.
2. Business Development: Exploring market opportunities and competitive analysis with automation tools to streamline workflows.
3. Manufacturing & Engineering: Understanding operations and using automation to improve efficiency and scalability.
4. Innovation Management: Collaborating with cross-functional teams to develop data-driven product improvements and automate processes.
By the end of the program, interns will have gained valuable insights into these areas and honed their ability to work independently, leverage automation, and deliver measurable results.
Job Responsibilities in Detail
1. Strategic Development
  • Define Strategic Issues: Analyze and articulate core problems or opportunities using advanced analytics.
  • Research and Analysis: Implement data collection pipelines and apply statistical and machine learning models for actionable insights.
  • Strategic Implications: Assess short-term and long-term effects of strategic options using predictive analytics and scenario modeling.
  • Actionable Recommendations: Present findings with automation-enhanced dashboards and clear action plans.
  • Execution: Implement strategies and monitor outcomes using automated tracking systems.

2. Data Analytics and Automation
  • Advanced Analytics: Use tools such as Python, R, SQL, or Power BI to analyze large datasets, model trends, and generate insights.
  • Automation: Identify repetitive tasks and implement process automation using tools like UiPath, Microsoft Power Automate, or custom scripts.
  • Quality Assurance: Ensure the accuracy and consistency of data-driven decisions by automating validation processes.
  • Cross-Functional Collaboration: Support decision-making with real-time, automated reporting shared across teams.

3. Innovation Team Engagement
  • Collaborate with multi-functional innovation teams to:
  • Develop value propositions for products and services using analytics and automation.
  • Forecast market opportunities with predictive modeling and automated data pipelines.
  • Conduct competitive assessments using automation tools to collect and analyze competitor data.

Qualities of a Successful Intern
  • Analytical Expertise: Strong ability to use data to identify patterns, solve problems, and inform strategies.
  • Automation Skills: Proficiency in identifying opportunities for process automation and implementing solutions.
  • Independence: Ability to manage work autonomously within a complex, global organization.
  • Organizational Skills: Effectively prioritize tasks and manage time to meet deliverables.
  • Judgment and Decision-Making: Use advanced analytics and automation tools combined with intuition to assess data and make sound recommendations.
  • Communication Skills: Clearly present updates, recommendations, and insights using automated dashboards and reports.
  • Collaboration: Work effectively with cross-functional teams, including business, operations, and technology leaders.

Education:
Bachelors