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Internship Machine Learning Jobs in Raleigh, NC (NOW HIRING)

SINNOVATEK SERVICES LLC

Automations Engineer

Middlesex, NC · On-site

$95K - $125K/yr

... machine learning models. ● Work on projects using Python, C++, or similar to interface with ... Prior internships, capstone projects, or personal projects involving automation, robotics, or ...

NCSU

Temporary IT Analyst / Programmer II

Raleigh, NC

$30 - $39/hr

This role involves managing multiple interns who will contribute to software development along specific pathways, including a Machine Learning Operations (MLOps) pathway. This pathway will bridge ...

NCSU

Lecturer of Data Science

Raleigh, NC

$4.0K/wk

Data Internships Preparation for Social Impact * Exploring Machine Learning Appointments will be for one or two semesters with the possibility of renewal. Note that this position is only for teaching ...

NCSU

Lecturer of Data Science

Raleigh, NC · On-site

$4.0K/wk

Data Internships Preparation for Social Impact * Exploring Machine Learning Appointments will be for one or two semesters with the possibility of renewal. Note that this position is only for teaching ...

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All JobsMachine Learning JobsInternship Machine Learning JobsInternship Machine Learning Jobs in Raleigh, NC

Internship Machine Learning information

See Raleigh, NC salary details

$24.8K

$41.4K

$85.5K

How much do internship machine learning jobs pay per year?

As of Sep 9, 2026, the average yearly pay for internship machine learning 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 is an internship machine learning?

Internship machine learning positions are temporary roles for students or recent graduates to gain hands-on experience in the field of machine learning. Interns typically work on real-world projects involving data analysis, model development, and algorithm implementation under the guidance of experienced professionals. These internships provide valuable exposure to machine learning tools, programming languages such as Python, and industry best practices. They are an excellent way to build technical skills, enhance your resume, and explore career opportunities in artificial intelligence and data science.

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

As a Machine Learning intern, you may work on a variety of projects such as data preprocessing and cleaning, developing and testing machine learning models, or assisting with research experiments. These projects often involve collaborating closely with data scientists and engineers, learning to use popular frameworks like TensorFlow or PyTorch, and presenting your findings to the team. The scope and complexity of your assignments will typically grow as you demonstrate proficiency and initiative, providing valuable real-world experience and networking opportunities.

What are the key skills and qualifications needed to thrive as an internship machine learning?

To thrive as a Machine Learning Intern, you generally need a solid grounding in mathematics, programming (especially Python), and familiarity with machine learning concepts, often supported by coursework or relevant projects. Experience with tools and libraries like TensorFlow, scikit-learn, and Jupyter Notebooks, as well as knowledge of version control systems like Git, is typically expected. Strong problem-solving skills, willingness to learn, and effective communication set outstanding interns apart. These skills and qualities enable interns to contribute meaningfully to projects, adapt quickly, and collaborate well within technical teams.

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

AspectInternship Machine LearningData Science Intern
Required CredentialsBasic programming, introductory ML knowledgeStatistics, programming, data analysis basics
Work EnvironmentHands-on ML model development, codingData analysis, visualization, reporting
Industry UsageTech, AI companies, research labsBusiness, finance, healthcare sectors

Internship Machine Learning focuses on developing and implementing machine learning models, requiring programming and ML fundamentals. Data Science Internships involve analyzing data, creating reports, and supporting decision-making. Both roles are common in tech and research industries, but ML internships are more specialized in model building, while Data Science internships emphasize data analysis and visualization.

What are the most commonly searched types of Machine Learning jobs in Raleigh, NC?

The most popular types of Machine Learning jobs in Raleigh, NC are:

What are popular job titles related to Internship Machine Learning jobs in Raleigh, NC?

For Internship Machine Learning jobs in Raleigh, NC, the most frequently searched job titles are:

What job categories do people searching Internship Machine Learning jobs in Raleigh, NC look for?

The top searched job categories for Internship Machine Learning jobs in Raleigh, NC are:

What cities near Raleigh, NC are hiring for Internship Machine Learning jobs?

Cities near Raleigh, NC with the most Internship Machine Learning job openings:

Internship Machine Learning jobs near you
Infographic showing various Internship Machine Learning job openings in Raleigh, NC as of September 2026, with employment types broken down into 43% Internship, and 57% Full Time. Highlights an 100% In-person job distribution, with an average salary of $41,395 per year, or $19.9 per hour.

Automations Engineer

Middlesex, NC • On-site

SINNOVATEK SERVICES LLC
See more jobs at SINNOVATEK SERVICES LLCexternal

$100 - $125/hr

Other

Re-posted 10 days ago

Job description

If you are unable to complete this application due to a disability, contact this employer to ask for an accommodation or an alternative application process.

Automations Engineer

Full Time Professional Middlesex, NC, US

3 days ago Requisition ID: 1144

Salary Range: $95,000.00 To $125,000.00 Annually

Duties and Responsibilities:
  • Assist in the design, modeling, and prototyping of process and packaging systems.
  • Support testing, assembly, and commissioning of prototypes under supervision.
  • Read and interpret mechanical drawings, electrical schematics, and process flow diagrams.
  • Specify, install, and troubleshoot sensors, actuators, and instrumentation for food manufacturing systems.
  • Participate in wiring, panel layout, and field testing activities.
  • Support integration, programming, and troubleshooting of PLC/HMI and SCADA systems.
  • Contribute to coding and testing of automation or AI-driven routines (predictive maintenance, data monitoring, optimization).
  • Assist with sensor data collection, labeling, and preprocessing for machine learning models.
  • Work on projects using Python, C++, or similar to interface with hardware systems.
  • Maintain accurate documentation including test reports, wiring diagrams, and engineering logs.
  • Ensure safe and organized work areas in labs and on production floors.
  • Participate in system commissioning and troubleshooting at customer sites when required.
  • Uphold SQF requirements including promotion of a strong & positive food safety culture
  • Active involvement in implementation, upkeep and continuous improvement of food safety as part of an interdisciplinary team
  • Stewardship for our B-corp mission to promote worldwide health and wellness by fostering the delivery of high quality, healthy foods through sustainable methods.
What You’ll Learn:
  • How to develop and test automated food manufacturing equipment
  • Machine learning integration in industrial environments
  • Industry codes, standards, and best practices (UL, CE, ISA, etc.)
  • Real-world project execution from concept to commissioning
  • Microwave and other electrical thermal processing technologies
Required:
  • Bachelor’s degree in Mechanical, Electrical, Automation, Mechatronics, Robotics, Computer Science, or a related engineering field (or graduation within 6 months).
  • Introductory experience or coursework in:
    • CAD (SolidWorks or AutoCAD)
    • Instrumentation and control systems
  • Controls integration with field devices (sensors, VFDs, flow meters, actuators).
  • Strong understanding of industrial communication protocols (EtherNet/IP, Modbus TCP, OPC UA).
  • Ability to troubleshoot electrical/automation systems in a production environment.
  • Hands-on mindset; comfortable using tools and learning in the field.
  • Strong communication, collaboration, and organizational skills.
  • Curiosity and eagerness to learn from a multidisciplinary team.
  • Active passport or ability to obtain one within the first 6 months.
Preferred (but not required):
  • Minimum of 2 years’ experience in automation, instrumentation, or controls engineering.
  • Familiarity with SCADA/HMI systems (Ignition, Wonderware, or WinCC).
  • Experience with data collection and integration from PLC/SCADA systems into historians, MES, or
  • Working knowledge of machine learning concepts and data analytics (TensorFlow, PyTorch, scikit-
  • learn, SQL).
  • Practical applications of ML in industrial settings (predictive maintenance, anomaly detection, process optimization).
  • Experience developing middleware or APIs to connect automation platforms with data pipelines.
  • Prior internships, capstone projects, or personal projects involving automation, robotics, or controls.
  • Basic electronics experience (soldering, sensor setup, instrumentation wiring).
  • Knowledge of OSHA safety standards and industrial safety practices.
  • Experience in food & beverage or other regulated manufacturing environments is a plus.
Physical Requirements:
  • Ability to work on the floor in a manufacturing setting; frequent walking and standing required.
  • Ability to work in hot, cold, or wet environments.
  • Specific vision abilities required by this job include close vision, distance vision, peripheral vision, depth perception, and ability to adjust focus.
  • Flexibility to alternate between hands‑on manufacturing work and office‑based programming/data analysis.
  • Comfortable working in environments with shifting priorities and ambiguity.
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