What are the responsibilities and job description for the Embedded Software Engineer Intern position at ENSCO, Inc.?
ENSCO, Inc. is seeking an enthusiastic Embedded Software Engineer Intern to support our Intelligence, Surveillance, and Reconnaissance (ISR) programs over the summer. This internship offers a unique opportunity to gain hands-on experience with real-time embedded systems, sensor integration, and signal processing applications, while contributing to mission-critical defense and intelligence projects under the mentorship of seasoned engineers.
Key Responsibilities:
Key Responsibilities:
- Software Development & Integration:
Assist in the design and integration of real-time embedded software using C, C , and Python across Linux, RTOS, and bare-metal platforms. - Device & Board Support:
Support device driver development and board bring-up for ARM, DSPs, and microcontrollers, learning industry best practices along the way. - Networking & Communication:
Help implement and troubleshoot networking protocols such as TCP/UDP/IP, CAN, SPI, I2C, and RS232 in a supervised setting. - Debugging & Testing:
Collaborate on hardware/software integration, debugging, and performance tuning initiatives. Contribute to developing automated test frameworks to validate and verify software functionalities. - Team Collaboration:
Work closely with senior engineers to explore sensor fusion, signal processing, and data acquisition techniques. Gain exposure to modern development tools, version control systems (Git), and CI/CD pipelines.
- Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field.
- Familiarity with programming in C, C , and Python; exposure to Linux environments (including embedded Linux) is a plus.
- Demonstrated academic performance and a strong interest in real-time software development, multi-threading, and working within resource-constrained environments.
- Excellent problem-solving skills, strong communication abilities, and eagerness to learn in a fast-paced engineering environment.
- Experience or coursework involving embedded Linux build systems such as Yocto or Buildroot.
- Exposure to sensor integration, signal processing, or data acquisition through projects or academic work.
- Familiarity with FPGA programming, CUDA, or hardware acceleration techniques.
- Interest in exploring Edge AI implementations (e.g., using TensorFlow Lite) or real-time Linux optimizations on ARM devices.