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Internship Manufacturing Systems Engineering Jobs

Manufacturing Systems Engineer

Boulder, CO ยท On-site

$70K - $75K/yr

Responsibilities Summary: The Manufacturing Systems Engineer is responsible for utilizing ... Bachelor's degree in computer science, engineering or related field or equivalent experience.

Bachelor's degree in computer science, engineering or related field or equivalent experience ... The Manufacturing Systems Engineer is responsible for utilizing, modifying, improving, and further ...

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Internship Manufacturing Systems Engineering information

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$11

$19

$29

How much do internship manufacturing systems engineering jobs pay per hour?

As of Jun 7, 2026, the average hourly pay for internship manufacturing systems engineering in the United States is $19.31, according to ZipRecruiter salary data. Most workers in this role earn between $16.11 and $20.91 per hour, depending on experience, location, and employer.

What is an Internship in Manufacturing Systems Engineering?

An Internship in Manufacturing Systems Engineering is a temporary position that provides students or recent graduates with hands-on experience in designing, analyzing, and improving manufacturing processes and systems. Interns typically work under the supervision of experienced engineers to learn about production workflows, automation, quality control, and process optimization. This internship helps participants develop practical skills, apply classroom knowledge to real-world scenarios, and gain insight into potential career paths in manufacturing engineering. It is a valuable opportunity to build a professional network and enhance employability in the engineering field.

What types of projects do Manufacturing Systems Engineering interns typically work on, and how do they contribute to the team?

Manufacturing Systems Engineering interns often work on projects that involve process optimization, automation, and data analysis to improve production efficiency. These projects may include mapping workflows, implementing lean manufacturing techniques, or assisting with the integration of new technologies. Interns collaborate closely with engineers, technicians, and production staff, gaining hands-on experience in problem-solving and process improvement. This exposure provides valuable insight into real-world manufacturing challenges and helps interns develop both technical and teamwork skills.

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

To thrive as an Internship Manufacturing Systems Engineer, you need a solid understanding of engineering principles, manufacturing processes, and problem-solving skills, typically supported by coursework toward a relevant engineering degree. Familiarity with CAD software, data analysis tools, and Lean Manufacturing or Six Sigma methodologies is often expected. Strong communication, teamwork, and analytical thinking distinguish top candidates in this role. These skills are crucial for improving production efficiency, collaborating across teams, and contributing innovative solutions to manufacturing challenges.

What is the difference between Internship Manufacturing Systems Engineering vs Manufacturing Engineer?

AspectInternship Manufacturing Systems EngineeringManufacturing Engineer
CredentialsEnrolled in or recent graduate of engineering or related programBachelor's degree in manufacturing, industrial, or mechanical engineering
Work EnvironmentInternship setting, often in manufacturing plants or corporate officesFull-time role in manufacturing facilities or design offices
Employer & IndustryManufacturing companies, internships for training and developmentManufacturing firms, responsible for process improvement and production

Internship Manufacturing Systems Engineering provides hands-on experience for students or recent graduates, focusing on learning manufacturing processes. Manufacturing Engineers are full-time professionals responsible for optimizing production systems, implementing improvements, and ensuring efficiency. The internship is a temporary learning position, while the manufacturing engineer role is a permanent position with greater responsibilities.

More about Internship Manufacturing Systems Engineering jobs
What cities are hiring for Internship Manufacturing Systems Engineering jobs? Cities with the most Internship Manufacturing Systems Engineering job openings:
What are the most commonly searched types of Manufacturing Systems Engineering jobs? The most popular types of Manufacturing Systems Engineering jobs are:
What states have the most Internship Manufacturing Systems Engineering jobs? States with the most job openings for Internship Manufacturing Systems Engineering jobs include:
What job categories do people searching Internship Manufacturing Systems Engineering jobs look for? The top searched job categories for Internship Manufacturing Systems Engineering jobs are:
Infographic showing various Internship Manufacturing Systems Engineering job openings in the United States as of May 2026, with employment types broken down into 17% Internship, 75% Full Time, and 8% Part Time. Highlights an 92% In-person, and 8% Remote job distribution, with an average salary of $40,174 per year, or $19.3 per hour.
AI Operations Internship - Manufacturing Systems

AI Operations Internship - Manufacturing Systems

Power Integrations

San Jose, CA โ€ข On-site

$32 - $34/hr

Other

Posted 13 hours ago


Job description

AI Operations Internship - Manufacturing Systems (2Month Term)
1) Internship Summary
We are offering an AI Operations Internship focused on rapidly advancing practical AI enablement within our manufacturing and test environments. The intern will join an active working team inside Operations, contributing to handson initiatives that improve visibility, data readiness, and system connectivity at the factory floor level.
This role is designed to deliver real, usable building blocks for AIdriven manufacturing-not longterm research. The intern's work will help move AI initiatives from concept toward deployment by improving equipment connectivity, traceability foundations, and data flow into manufacturing systems.

2) Responsibilities
  • Work across Test Engineering and Product Engineering, with regular interaction with manufacturing operations.
  • Report directly to the Principal Test Engineer in charge of Test Engineer Services as well as guidance from a Sr. Product Engineer.
  • Focus on data connectivity, basic analytics enablement, and system groundwork, using AIassisted coding tools to rapidly prototype, automate, and iterate.
  • Document assumptions, interfaces, and lessons learned to support followon work after the internship concludes.

3) Key Deliverables
Within the limited internship timeframe, the intern will deliver the following wellbounded, achievable outputs:
  • Test Handler Connectivity & Visibility
    • Assist in networking ATE handlers and related equipment to enable basic data capture and visibility of test output and utilization as well as error codes.
    • Support simple data views or summaries to illustrate opportunities for throughput optimization.
  • Predictive Maintenance Groundwork
    • Help identify and organize available equipment signals and maintenance logs.
    • Prepare cleaned datasets or dashboards that could later support predictive maintenance efforts (no fault correlation or modeling required).
  • DieLevel Traceability Foundations
  • Research and support early concepts for dielevel traceability, including evaluating camera retrofit options on test handlers for 2D barcode capture and understanding how this capability would fit within the existing handler architecture.
  • Help validate image capture workflows for 2D barcodes that provide full dielevel traceability within packages, and assist in defining how this traceability information can be uploaded into YMS (Yield Management System).

Qualifications & Requirements
Required Skills:
  • Basic programming ability (e.g., Python, MATLAB, or similar) for scripting, data handling, and prototyping
  • Familiarity with data handling and basic analytics (CSV/JSON files, simple plots, tables, summaries)
  • Ability to work with hardwareadjacent systems (equipment, sensors, test systems) at a conceptual level
  • Comfort using AIassisted coding tools (e.g., Copilotstyle tools, LLMs for code generation and debugging)
  • Strong analytical thinking and ability to document system assumptions and data flows clearly
Preferred Skills:
  • Handson experience with hardware projects, such as senior design, robotics, or lab work involving sensors, cameras, or physical system modifications
  • Exposure to mounting or retrofitting hardware components (e.g., cameras, fixtures, brackets) and working within mechanical constraints
  • Experience interfacing hardware with software using USB, Ethernet, serial, or basic I/O connections
  • Familiarity with camera setup for reliable image capture (field of view, focus, lighting, triggering), without requiring computer vision or barcode decoding expertise
  • Experience with data logging or lab instrumentation, including adding metadata to logs or associating data across systems
  • Comfort working in handson, iterative environments where documentation may be incomplete and practical problemsolving is required
Education Level:
3 or 4 year engineering student with clear career objectives
Fields of Study
  • Electrical Engineering
  • Computer Engineering
  • Computer Science
  • Mechanical Engineering (with automation, controls, or mechatronics focus)
  • Industrial Engineering
  • Robotics or Mechatronics
  • Applied AI or Data Science (systems or hardwareoriented programs)
Power Integrations is committed to building teams that drive innovation and therefore review a range of factors when determining compensation.The hourly pay range for this internship is $32 to $34. Our pay ranges are determined by role, level, qualifications and work location.
The range displayed on the job posting reflects the minimum and maximum target for this intern in California. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training.