Spring 2027 Machine Learning Co-Op
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Summary
An on-site Spring 2027 co-op in Parsippany, NJ supporting a machine learning project in Marotta Controls' Power and Actuation Systems business unit. The student collects and cleans engineering data, builds and evaluates ML models in Python, documents findings, and presents results to leadership, with a path to continue into Summer 2027.
Elevate your career at Marotta Controls, a New Jersey Top Workplace four years running! Dedicated to innovation, quality and excellence, we deliver cutting edge control systems for the Aerospace & Defense industry. At Marotta, we value bold thinking and teamwork, and we empower our employees to push boundaries while delivering top-tier solutions to our customers. Our team fosters a fun, collaborative culture where creativity and technical excellence thrive! Your next big opportunity starts here. Be part of a company where your work supports a mission that makes a difference—apply today!
Spring/Summer 2027 Machine Learning Co-Op
About the Program
Join Marotta Controls’ Co-Op Program and take your classroom knowledge into the real world of aerospace and defense. As a Machine Learning Co-Op, you’ll gain hands-on experience supporting an business project focused on machine learning and data-driven technology while working alongside experienced technical professionals.
During your rotation, you’ll help explore, develop, test, and evaluate machine learning solutions that can support business applications and needs within the Power and Actuation Systems Business Unit. You’ll apply programming, data analysis, and machine learning concepts to a real-world project while gaining exposure to aerospace and defense engineering. You’ll receive mentorship throughout the program and present your project, results, and key learnings to senior leadership at the end of your rotation. Along the way, you’ll also network with other interns and employees through professional development, technical learning, and engagement events.
Location: Parsippany, NJ (On‑Site Monday - Friday)
Term: Spring 2027 with the opportunity to continue into Summer 2027
Business Unit: Power and Actuation Systems
Term: Spring 2027 with the opportunity to continue into Summer 2027
Business Unit: Power and Actuation Systems
Potential for Full-Time Employment
Our Co-Op program provides an opportunity to gain hands-on experience, develop valuable technical and professional skills, and potentially transition into a full-time position based on performance and organizational needs.
What You’ll Do
- Support the development and implementation of a machine learning project.
- Collect, organize, clean, and analyze engineering data for use in machine learning models.
- Develop, train, test, and evaluate machine learning algorithms and models.
- Write and maintain code used for data processing, analysis, model development, and testing.
- Evaluate model performance and help identify opportunities to improve accuracy, efficiency, and reliability.
- Create visualizations and technical summaries to communicate findings and project results.
- Document methodologies, assumptions, test results, and technical findings.
- Collaborate with engineering and cross-functional teams to understand project requirements and translate business or technical problems into data-driven solutions.
- Present project progress and final results to engineering leadership and other stakeholders.
What We’re Looking For
- Currently enrolled in a Data Science, Computer Engineering, Computer Science, Electrical Engineering, Software Engineering, or related technical degree program.
- Strong GPA and demonstrated performance in core engineering, computer science, mathematics, or programming coursework.
- Coursework or hands-on experience in machine learning, artificial intelligence, data science, or statistical modeling.
- Programming experience with Python.
- Familiarity with common data analysis or machine learning libraries such as NumPy, Pandas, scikit-learn.
- Understanding of fundamental machine learning concepts such as supervised and unsupervised learning, model training, validation, and performance evaluation.
- Experience working with datasets, performing data analysis, or developing technical projects through coursework, research, or personal projects.
- Strong analytical and problem-solving skills.
- Detail-oriented, precise, organized, and comfortable documenting technical work.
- Strong written and verbal communication skills with the ability to explain technical concepts and findings.
- Ability to work effectively both independently and as part of a multidisciplinary engineering team.
- U.S. Citizenship required.
- Availability to work full-time onsite beginning January 2027 through the end of Summer 2027.
Preferred Qualifications
- Experience developing a machine learning or artificial intelligence project through coursework, research, competitions, or personal projects.
- Interest in applying machine learning technologies to aerospace, defense, manufacturing, test, or engineering applications.
- Familiarity with TensorFlow, or PyTorch.
Work Environment
- This job interacts both in a professional office environment and a manufacturing/machine shop environment.
- This role uses standard office equipment such as computers, phones, photocopiers, filing cabinets, and other engineering tools and equipment.
- The employee may work in environments requiring appropriate eye, hearing, and foot protection, as required.
Physical Requirements
- While performing the duties of this job, the employee is regularly required to see, talk, and hear.
- The Engineering Intern/Co-Op is frequently required to reach with hands and arms and to use hands to finger, handle, or feel.
- The Engineering Intern/Co-Op is frequently required to sit for extended periods, stand, walk, and move throughout the facility.
- The Engineering Intern/Co-Op may be required to lift and/or move items weighing up to 20 pounds.
Why Marotta?
At Marotta, you’ll contribute to programs that support space exploration, defense readiness, and advanced aerospace systems. This Co-Op gives you the opportunity to work on an emerging technology project with real engineering applications while developing practical experience in machine learning, data analysis, software development, and aerospace engineering.
Your work will matter, and you’ll gain practical skills that can help launch your engineering career.
Position location Parsippany, NJ
Relocation assistance will not be provided.
Pay Range: $18 - $24/hr
Many of our contracts require proof that you are a U.S. citizen and/or that an export license has been obtained for employees who are citizens of certain countries. Your employment, both initially and continually thereafter, is conditioned on production of such proof of citizenship and/or any export license that may be required to comply with any and all applicable laws, regulations, or executive orders, or required by Federal, State, or local government contracts.
At Marotta Controls, we are committed to a fair, performance-driven compensation approach that promotes consistency across all levels of our organization. We ensure that pay decisions are free from bias, based on objective criteria, and are regularly reviewed.
Your level and base salary will be determined on a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, experience, and internal consistency.
Additionally, we offer a highly competitive compensation package for this opportunity, including incentive compensation and a comprehensive suite of premium benefits. These include medical, prescription, dental, vision, life, and disability insurance, a 401(k) plan with company match, tuition assistance, paid vacation, sick and personal days, paid holidays, and flexible scheduling options such as compressed workweeks. We value and reward employee achievements and host multiple engagement events each quarter to foster a strong, supportive workplace culture.
Please visit our website at to learn more about us and to apply. Check out all our openings at
VETERANS ARE ENCOURAGED TO APPLY
No agencies, please.
