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Internship Machine Learning Engineer Jobs in Raleigh, NC

OptiTrack

Machine Learning & Operations Engineer

Durham, NC · Remote

$71.10K - $96.20K/yr

About the Role OptiTrack is seeking a Machine Learning Engineer to help design, automate, and scale an MLOps system and provide other support to teams working on projects involving machine learning.

OptiTrack

Machine Learning & Operations Engineer

Durham, NC · Remote

$67.20K - $90.80K/yr

About the Role OptiTrack is seeking a Machine Learning Engineer to help design, automate, and scale an MLOps system and provide other support to teams working on projects involving machine learning.

Apple

AIML - Staff Machine Learning Engineer

Cary, NC · On-site

Building this system requires deep expertise in a myriad of cutting edge fields: search, natural language understanding, data engineering, machine learning, privacy preserving system design, and more.

RELX

Principal Machine Learning Engineer I

Raleigh, NC

$136.10K - $252.80K/yr

We are seeking a Principal Machine Learning Engineer to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products.

LexisNexis

Principal Machine Learning Engineer I

Raleigh, NC · On-site

$136.10K - $252.80K/yr

We are seeking a Principal Machine Learning Engineer to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products.

Apple

AIML - Staff Machine Learning Engineer

Cary, NC

$212K - $386.30K/yr

Building this system requires deep expertise in a myriad of cutting edge fields: search, natural language understanding, data engineering, machine learning, privacy preserving system design, and more.

Apple

AIML - Staff Machine Learning Engineer

Cary, NC

$212K - $386.30K/yr

Building this system requires deep expertise in a myriad of cutting edge fields: search, natural language understanding, data engineering, machine learning, privacy preserving system design, and more.

Qualcomm

Machine Learning Compiler

Raleigh, NC · On-site

$160.60K - $240.80K/yr

Engineering Group, Engineering Group > Machine Learning Engineering General Summary: Lead a team of engineers focused on advancing machine learning compiler technologies for cutting-edge AI ...

Varsity Tutors

Machine Learning Tutor

Chapel Hill, NC · Remote

$40/hr

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

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Internship Machine Learning Engineer information

See Raleigh, NC salary details

$24.8K

$41.4K

$85.5K

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

As of May 30, 2026, the average yearly pay for internship machine learning engineer in Raleigh, NC is $41,395.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,600.00 and $44,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Internship Machine Learning Engineer, and why are they important?

To excel as an Internship Machine Learning Engineer, you typically need a solid background in mathematics, programming (especially Python), and foundational machine learning concepts, often supported by coursework or relevant project experience. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is common, along with proficiency in data processing libraries. Curiosity, strong problem-solving abilities, and effective teamwork and communication skills help set candidates apart. These competencies ensure you can contribute meaningfully to projects, adapt to new challenges, and collaborate productively in a rapidly evolving technical environment.

What types of projects and responsibilities can I expect as an Internship Machine Learning Engineer?

As an Internship Machine Learning Engineer, you will typically support the development, testing, and deployment of machine learning models under the guidance of senior engineers. Your responsibilities may include data preprocessing, exploratory data analysis, implementing algorithms, and evaluating model performance. You'll often collaborate closely with data scientists, software engineers, and product managers, gaining exposure to real-world workflows and tools. This hands-on experience is invaluable for building technical skills and understanding how machine learning solutions are integrated into larger products.

What does an Internship Machine Learning Engineer do?

An Internship Machine Learning Engineer works alongside experienced engineers to help develop, test, and deploy machine learning models. Their responsibilities may include cleaning and preparing data, writing code for model training, evaluating model performance, and contributing to research tasks. Interns often learn to use popular frameworks such as TensorFlow or PyTorch and gain hands-on experience with real-world datasets. This role is designed to help students or recent graduates apply their academic knowledge to practical problems while developing industry-relevant skills.

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

AspectInternship Machine Learning EngineerData Scientist Intern
Required CredentialsBasic programming, introductory ML knowledgeStatistics, data analysis, programming
Work EnvironmentDeveloping ML models, coding, testingData analysis, visualization, reporting
Employer & Industry UsageTech companies, startups, AI firmsTech, finance, healthcare, consulting

Internship Machine Learning Engineers focus on developing and testing machine learning models, often requiring programming and basic ML knowledge. Data Scientist Interns analyze data, create visualizations, and generate insights. Both roles are common in tech and data-driven industries, but ML Engineer internships emphasize model deployment, while Data Science internships focus on data analysis and reporting.

What are the most commonly searched types of Machine Learning Engineer jobs in Raleigh, NC? The most popular types of Machine Learning Engineer jobs in Raleigh, NC are:
Internship Machine Learning Engineer jobs near you
Infographic showing various Internship Machine Learning Engineer job openings in Raleigh, NC as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% Hybrid job distribution, with an average salary of $41,395 per year, or $19.9 per hour.
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Western Governors University

Raleigh, NC • On-site

$157K - $243.40K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted yesterday

Western Governors University rating

8.6

Company rating: 8.6 out of 10

Based on 41 frontline employees who took The Breakroom Quiz

49th of 529 rated colleges and universities

Job description

If you're passionate about building a better future for individuals, communities, and our country-and you're committed to working hard to play your part in building that future-consider WGU as the next step in your career.
Driven by a mission to expand access to higher education through online, competency-based degree programs, WGU is also committed to being a great place to work for a diverse workforce of student-focused professionals. The university has pioneered a new way to learn in the 21st century, one that has received praise from academic, industry, government, and media leaders. Whatever your role, working for WGU gives you a part to play in helping students graduate, creating a better tomorrow for themselves and their families.
The salary range for this position takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.
At WGU, it is not typical for an individual to be hired at or near the top of the range for their position, and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is:
Grade: Technical 411
Pay Range: $157,000.00 - $243,400.00
Job Description
The Senior ML Engineer builds and deploys state-of-the-art NLP/LLM models at scale in a cloud environment, with a focus on improving student learning experiences. You lead by example, mentor junior engineers, and collaborate across cross-functional teams. You actively research the latest NLP/LLM techniques and translate them into practical, scalable solutions for the education domain. You communicate clearly with leadership and peers, influence product directions, and drive innovation that challenges the status quo.
Key Responsibilities
  • Strategic leadership

  • Define NLP initiatives, roadmaps, and success metrics in collaboration with the MLE manager.

  • Champion best practices in ML, data governance, and security within the team and across the organization.

  • Mentor junior engineers and serve as a technical lead on complex ML projects.

  • Model research, development, and deployment

  • Research and prototype state-of-the-art NLP/LLM techniques; evaluate and select approaches suitable for production.

  • Develop, train, fine-tune, and optimize production-grade NLP/LLM models.

  • Deploy models to production with emphasis on performance, scalability, reliability, and observability.

  • Data, pipelines, and collaboration

  • Partner with Data Engineering to build robust data processing pipelines and high-quality training/inference data.

  • Work with MLOps to ensure scalable, reproducible deployment, monitoring, and model governance.

  • Collaborate with Software, Infrastructure, and Security teams to integrate ML solutions into the university ecosystem.

  • Product impact and stakeholder engagement

  • Translate business requirements into NLP capabilities; collaborate with product stakeholders to validate outcomes.

  • Apply NLP insights to unstructured data sources (e.g., transcripts, emails, mentor notes) to inform learning experiences.

  • Continuous improvement and learning

  • Stay current with NLP/LLM, DL, and AI trends; proactively apply innovations to use cases.

  • Contribute to standards, guidelines, and documentation for ML practices.

  • Communicate status, risks, and progress to leadership and cross-functional teams.

Minimum Qualifications:
  • Master's degree in Computer Science, Software Engineering, Data Science, Machine Learning, Mathematics, Physics, or a related field; or equivalent relevant experience.

  • 5+ years of software development in a cloud environment.

  • 3+ years building large-scale ML/DL models, from POC to production.

  • Hands-on experience with one or more DL frameworks (e.g., PyTorch, TensorFlow).

  • Experience with cloud data platforms (AWS, Azure, GCP) and data/ML tooling (e.g., Databricks, MLFlow, Streamlit).

  • Proficiency in ETL, feature engineering, data visualization.

  • Experience operating high-availability, fault-tolerant, scalable distributed systems with GitOps practices (Terraform preferred).

  • Familiarity with stream processing (ksqlDB, Spark Streaming, Beam/Flink) and modern ML deployment patterns.

  • Strong programming skills in Python, Java/Scala, and/or Go; fluency in clean, maintainable code.

  • Excellent analytical, critical thinking, and problem-solving abilities.

  • Effective written and verbal communication; comfortable explaining technical concepts to non-experts and senior leadership.

  • Ability to thrive in a fast-paced, collaborative environment.

  • Experience guiding junior engineers and providing technical leadership.

Preferred Qualifications
  • PhD in a related field.

  • Experience with Databricks and a broad range of ML tooling.

Equivalents and Substitutions
  • Equivalent relevant experience may substitute for degree requirements (1 year of experience per year of education at the discretion of the Hiring Manager).

#LI-GB1
Position & Application Details
Full-Time Regular Positions (classified as regular and working 40 standard weekly hours): This is a full-time, regular position (classified for 40 standard weekly hours) that is eligible for bonuses; medical, dental, vision, telehealth and mental healthcare; health savings account and flexible spending account; basic and voluntary life insurance; disability coverage; accident, critical illness and hospital indemnity supplemental coverages; legal and identity theft coverage; retirement savings plan; wellbeing program; discounted WGU tuition; and flexible paid time off for rest and relaxation with no need for accrual, flexible paid sick time with no need for accrual, 11 paid holidays, and other paid leaves, including up to 12 weeks of parental leave.
How to Apply: If interested, an application will need to be submitted online. Internal WGU employees will need to apply through the internal job board in Workday.
Additional Information
Disclaimer: The job posting highlights the most critical responsibilities and requirements of the job. It's not all-inclusive.
Accommodations: Applicants with disabilities who require assistance or accommodation during the application or interview process should contact our Talent Acquisition team at recruiting@wgu.edu.
Equal Employment Opportunity: All qualified applicants will receive consideration for employment without regard to any protected characteristic as required by law.

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