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Machine Learning Developer Intern Jobs in Charlotte, NC

Senior AI Machine Learning Engineer

Charlotte, NC ยท On-site

$119K - $157K/yr

Sr Data Engineer - GE07BE We're determined to make a difference and are proud to be an insurance ... The Hartfordis seeking aSenior AI Machine Learning Engineerwithin Employee Benefits Applied AI and ...

Engineering Intern We are looking for an Engineering (Technical) Intern for our Charlotte, NC site ... Support machine improvements, troubleshooting, & repairs * Research and procure materials from ...

Engineering Intern We are looking for an Engineering (Technical) Intern for our Charlotte, NC site ... Support machine improvements, troubleshooting, & repairs * Research and procure materials from ...

Engineer Intern

Charlotte, NC ยท On-site

$18 - $21/hr

Engineering Intern We are looking for an Engineering (Technical) Intern for our Charlotte, NC site ... Support machine improvements, troubleshooting, & repairs * Research and procure materials from ...

Engineer Intern

Charlotte, NC ยท On-site

$18 - $21/hr

Engineering Intern We are looking for an Engineering (Technical) Intern for our Charlotte, NC site ... Support machine improvements, troubleshooting, & repairs * Research and procure materials from ...

Showing results 41-60

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.

Sr. Machine Learning/AI Engineer

Financial Independence Group, LLC

Cornelius, NC โ€ข On-site

$96K - $132K/yr

Full-time

Re-posted 26 days ago


Job description

WHO WE ARE:

Financial Independence Group (FIG) is one of the nation's largest Finance and Insurance Marketing Organizations (FMO & IMO) in the country, partnering with thousands of financial professionals in all 50 states. FIG seeks to expand the availability of financial products and services to financial professionals and ultimately the clients and families they serve. This is accomplished through robust product offerings, innovative marketing, and cutting-edge technology.

Interested in learning more? Click here to find out what it's like to work at FIG.

ABOUT THE TEAM:

FIG's AI & Analytics Team is advancing the next generation of intelligent capabilities across the organization. We combine stateoftheart machine learning, modern data engineering, and agentdriven automation to enhance how FIG supports advisors, strengthens operations, and accelerates strategic decisionmaking.

We operate in a fastpaced, collaborative, and experimentationfriendly environment. Our team partners crossfunctionally with technology, operations, and business leaders to develop AI systems that deliver measurable impact, ranging from predictive models and enterprise automations to retrievalaugmented assistants and largescale generative AI solutions.

Innovation, iteration, and continuous improvement are core to how we work. We build, test, refine, and deploy AI capabilities that push boundaries and elevate FIG's intelligence ecosystem. As we scale the use of AI across the business, we also uphold strong governance, responsibleuse standards, and transparency to ensure our systems remain safe, ethical, and hightrust.

YOUR ROLE:

As a Senior Machine Learning/AI Engineer, you play a critical role in architecting, building, and operationalizing FIG's next generation of intelligent systems. You will develop productiongrade machine learning models, generative AI capabilities, and automated workflows that support advisors, enhance internal operations, and drive organizational efficiency.

You will:

  • Design, build, and deploy machine learning models and AI systems at scale.
  • Develop LLMpowered applications, including RAG pipelines, agent workflows, and automated decisionsupport tools.
  • Collaborate with crossfunctional partners to translate business needs into technical AI solutions.
  • Work closely with data engineering to ensure strong data availability, quality, and ML readiness.
  • Mentor engineers and analysts, guiding best practices in MLOps, model development, and responsible AI.
  • Implement monitoring, observability, and model governance frameworks.
  • Maintain high standards for security, safety, and compliance aligned with FIG's AI governance.
  • Evaluate new models, tools, and frameworks to continuously expand FIG's AI capabilities.
  • Present recommendations, insights, and solution designs to technical and nontechnical stakeholders.

WHY YOU ARE THE RIGHT PERSON:

  • You thrive in a fastpaced, highly collaborative environment.
  • You are a builder at heart-creative, curious, and excited by solving complex technical problems.
  • You blend strong engineering fundamentals with practical ML/AI expertise.
  • You understand how to design models that solve real business problems and scale effectively.
  • You are passionate about mentorship and leveling up the technical skillsets around you.
  • You communicate clearly and can explain complex concepts to nontechnical audiences.
  • You bring a forwardthinking mindset, constantly seeking opportunities to innovate and automate.
  • You embrace iteration and continuous improvement in everything you build.
  • You believe in responsible AI and understand the importance of governance, safety, and human oversight.

WHAT YOU BRING:

ย Technical Skills

  • Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, scikitlearn).
  • Experience building and deploying machine learning models into production environments.
  • Handson experience working with large language models (LLMs), transformers, vector databases, embeddings, and retrievalaugmented generation (RAG).
  • Ability to design endtoend AI pipelines from data ingestion and feature engineering to training, evaluation, deployment, and monitoring.
  • Familiarity with prompt engineering, finetuning, and model optimization techniques.
  • Experience implementing MLOps workflows and tools (MLflow, Databricks, Weights & Biases, SageMaker, AgentCore or similar).
  • Knowledge of agent frameworks (Strands, LangChain, Semantic Kernel, CrewAI, AutoGen).
  • Knowledge of cloud technologies (AWS preferred), containerization and orchestration.
  • Strong SQL skills and comfort working with modern data platforms (e.g., Snowflake, Redshift, BigQuery, Synapse).
  • Experience deploying APIs, microservices, and distributed systems.

ย Analytical Skills

  • Ability to evaluate model performance, identify failure modes, and optimize for accuracy, fairness, and reliability.
  • Strong criticalthinking skills paired with creativity in designing AIdriven solutions.
  • Experience conducting exploratory analysis, model experimentation, and error analysis.
  • Ability to balance technical excellence with practical business impact.

ย Business & Communication Skills

  • Ability to translate business needs into scalable AI solutions.
  • Experience partnering with crossfunctional teams across engineering, data, operations, and leadership.
  • Strong communication skills with the ability to present complex concepts clearly.
  • Ability to mentor, guide, and influence teammates and stakeholders.

Bonus Experience (Nice to Have)

  • Experience in financial services, insurance, wealth management, or other regulated industries.
  • Prior involvement in AI governance, responsible AI frameworks, or risk assessments.
  • Experience contributing to data governance, metadata management, or model lineage documentation.
  • Familiarity with experimentation frameworks, A/B testing, or statistical modeling.
  • Working knowledge of reinforcement learning, recommendation systems, or advanced NLP techniques.