Embedded Machine Learning Engineer Intern

Enovation Controls is a turnkey technology company that solves complex problems and delivers innovative electronic control and display solutions across diverse markets. People who find their place here tend to stay. Many of our team members have decades of tenure, evidence of a culture where people feel valued and want to build a career. 

We’re proud to be recognized by Great Place to Work as one of the Best Workplaces in Manufacturing & Production for seven consecutive years, as well as by Mployer Advisor for our Top U.S. Benefits. This recognition comes directly from employee feedback, not marketing, and reflects a workplace where people feel trusted, supported, and empowered. We live our core values every day in a collaborative, high-performance environment that balances complex technical work with real camaraderie, accessible leadership, and traditions that bring teams together.

About the Internship

Program Dates: May 24 – August 6

Schedule: Full-time, paid internship

Location: Onsite, Tulsa, OK

Are you an engineering or computer science student interested in combining machine learning with embedded systems? Join Enovation Controls as an Embedded Machine Learning Engineering Intern and explore how intelligent software can be integrated into electronic controls and display technologies.

In this role, you'll work alongside experienced engineers to explore, develop, and evaluate machine learning solutions for resource-constrained embedded platforms. You'll have the opportunity to apply your programming and analytical skills to real-world engineering challenges while gaining hands-on exposure to embedded software development, machine learning models, and system integration.

We're looking for a self-motivated, independent thinker with an entrepreneurial mindset who enjoys exploring new ideas, taking initiative, and figuring things out when the path forward isn't always clearly defined. This internship is ideal for someone who is comfortable working through ambiguity, experimenting with new approaches, and taking ownership of challenges from initial concept through testing and evaluation. If you're curious, resourceful, and excited to turn innovative ideas into practical solutions, we'd love to hear from you.

What You'll Work On

• Assist with developing and evaluating machine learning models for potential use in embedded systems.
• Explore techniques for deploying and running ML models on resource-constrained hardware.
• Support the integration of machine learning capabilities into embedded software applications.
• Collect, prepare, and analyze datasets for model development, testing, and evaluation.
• Evaluate model performance, accuracy, efficiency, and suitability for embedded applications.
• Investigate methods for optimizing models to reduce computational requirements, memory usage, and processing time.
• Develop scripts, prototypes, and tools to support model training, testing, and deployment.
• Document development processes, test results, and findings to support ongoing engineering efforts.
• Collaborate with software, hardware, and engineering teams to explore innovative technology applications.