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Machine Learning Developer Intern Jobs in Charlotte, NC

In this role, you will partner with Product, Engineering, Clinical,Operations, Marketing and Data Engineering to design, build, deploy, andoperatescalable machine learning and AI systems that power ...

Senior Machine Learning Test Engineer

Concord, NC · On-site +1

$102K - $133K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East ... You are a quality-focused developer who is passionate about reliable, repeatable evaluation of ML ...

The Hartford is seeking Senior AI Machine Learning Engineer to build Machine Learning Operations ... Master's degree in related field or 5+ years of equivalent experience in a research or DevOps ...

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

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

Showing results 21-40

Machine Learning Developer Intern information

See Charlotte, NC salary details

$24.9K

$41.6K

$86K

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

As of Aug 20, 2026, the average yearly pay for machine learning developer intern in Charlotte, NC is $41,592.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,700.00 and $44,900.00 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.

Machine Learning Engineer

Tihinsurance

Charlotte, NC

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 23 days ago


Job description

The position is described below. If you want to apply, click the Apply button at the top or bottom of this page. You'll be required to create an account or sign in to an existing one.

If you have a disability and need assistance with the application, you can request a reasonable accommodation. Send an email to Accessibility (accommodation requests only; other inquiries won't receive a response).

Regular or Temporary:

Regular

Language Fluency: English (Required)

Work Shift:

1st Shift (United States of America)

Please review the following job description:

We are building the foundation of the machine learning function at a market-leading insurance company. As one of the first data science hires, you will play a pivotal role in shaping our ML strategy, frameworks, and operating model. This is a unique opportunity to be hands-on, developing and maintaining production-grade solutions while influencing the long-term vision and scaling of our ML capabilities.

Key Responsibilities

Strategic Contribution

  • Partner with the Head of ML, product and data teams to define and implement the company-wide ML framework and best practices.

  • Contribute to the roadmap for ML development, adoption and team growth.

Hands-On Development

  • Ideate, design and build ML and AI prototypes to validate priority use cases and solve complex business problems to drive tangible value, while collaborating with product and business teams.

  • Develop and deploy production-grade ML models and data pipelines.

  • Build orchestration and integration frameworks for ML models and pipelines.

  • Develop and maintain CI/CD pipelines for ML solutions, including test automation, to ensure successful deployment of updated models

Operational Excellence

  • Monitor, maintain, and retrain models in production to ensure performance and compliance.

  • Manage data updates, versioning, and integrity for deployed solutions.

  • Implement robust monitoring and alerting systems for ML services.

Team Building

  • Help establish processes, tools, and standards for a growing ML team.

  • Mentor future hires and contribute to a collaborative, innovative culture.

ESSENTIAL DUTIES AND RESPONSIBILITIES
Following is a summary of the essential functions for this job. Other duties may be performed, both major and minor, which are not mentioned below. Specific activities may change from time to time.
1. Develop customized coding, software integration, perform analysis, configure solutions, using tools specific to the project or the area.
2. Lead and participate in the development, testing, implementation, maintenance, and support of highly complex solutions in adherence to company standards, including robust unit testing and support for subsequent release testing.
3. Build non-functional monitoring capabilities and provide escalated support for highly complex applications in production.
4. Build in and maintain security controls and monitoring in support of company standards.
5. Typically lead moderately complex projects and participate in larger, more complex initiatives.
6. Solve complex technical and operational problems. Act as a resource for teammates with less experience
7. May oversee the work of a small team.
8. In an Agile environment: Responsible for delivering high quality working software and automating manual/reusable tasks working directly, and engage with, the business from the beginning of the design work. Leverage continuous engineering practices to deliver business value regarding effectiveness of the design. Actively participate in refining user stories. Responsible for design, developing, and maintaining automated unit testing, and supporting integration and functional testing. Responsible for providing automated monitoring capabilities, providing warranty support, and providing knowledge transfer to production support. Develop code in accordance with the acceptance criteria established by the Product Owner.

QUALIFICATIONS
Required Qualifications:

The requirements listed below are representative of the knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
1. Bachelor's Degree and six to ten years of experience or equivalent education and software engineering training or experience

Technical Skills

  • Strong proficiency in Python and ML frameworks.

  • Experience with Databricks and Azure for data engineering and ML workflows.

  • Familiarity with MLOps tools (MLflow, Lakehouse Monitoring, Azure DevOps) and CI/CD practices.

  • Solid understanding of data science and engineering principles and model lifecycle management.

Experience

  • 5+ years total in data analytics, infrastructure, engineering and science roles.

  • 2+ years in applied ML engineering or data science roles.

  • Proven track record of deploying ML models into production environments.

  • Familiarity with monitoring, retraining, and maintaining ML systems at scale.

Soft Skills

  • Ability to work independently and collaboratively in a fast-paced environment.

  • Strong communication skills to influence stakeholders and explain technical concepts.

Nice-to-Have:

  • Knowledge of insurance industry data and business processes


2. In-depth knowledge in information systems and ability to identify, apply, and implement best practices
3. Understanding of key business processes and competitive strategies related to the IT function
4. Ability to plan and manage projects and solve complex problems by applying best practices
5. Ability to provide direction and mentor less experienced teammates. Ability to interpret and convey complex, difficult, or sensitive information

Location: Charlotte, Dallas, Raleigh, Alpharetta

General Description of Available Benefits for Eligible Employees of CRC Group: At CRC Group, we're committed to supporting every aspect of teammates' well-being - physical, emotional, financial, social, and professional. Our best-in-class benefits program is designed to care for the whole you, offering a wide range of coverage and support. Eligible full-time teammates enjoy access to medical, dental, vision, life, disability, and AD&D insurance; tax-advantaged savings accounts; and a 401(k) plan with company match. CRC Group also offers generous paid time off programs, including company holidays, vacation and sick days, new parent leave, and more. Eligible positions may also qualify for restricted stock unitsand/or a deferred compensation plan.

CRC Group supports a diverse workforce and is an Equal Opportunity Employer that does not discriminate against individuals on the basis of race, gender, color, religion, citizenship or national origin, age, sexual orientation, gender identity, disability, veteran status or other classification protected by law. CRC Group is a Drug Free Workplace.

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