Staff Engineer- Linux Application Developer

About Macnica:

Macnica Americas, Inc. is the North American division of Macnica Fuji Electronics Holdings, Inc. a $10 billion technology solutions provider with a stronghold in semiconductor distribution. Macnica excels in customizing solutions to client requirements and leveraging skilled engineers to expedite product development without compromising outcomes for our clients.

Company perks

• :15 days of vacation, plus 12 days of national holiday
• s40 hrs. of paid sick time of
• fHealth, dental, and vision insuranc
• e401 (k) with company matchin
• gHSA/ FS

A
Job Summar

y:We are seeking a highly skilled and experienced Staff Embedded Engineer to join our dynamic team. This role requires a proactive and hands-on professional with expertise in embedded systems, software development, multimedia frameworks, and protocol management. As a Staff Engineer, you will be involved in designing, developing, and maintaining advanced embedded systems while collaborating with cross-functional teams to achieve product milestone

s.
Responsibiliti

• es:Develop, implement, and maintain complex Linux applications, writing efficient code primarily in C/C or other relevant languages. Optimize applications for performance and reliability in resource-constrained environmen
• ts.Integrate Linux applications with various subsystems, including multimedia, network protocols, and device drivers, ensuring seamless communication and interoperabili
• ty.Analyze and optimize application performance at both software and system levels, using profiling tools and techniques to enhance responsiveness, stability, and resource usa
• ge.Provide solutions to complex issues in collaboration with other team membe
• rs.Work closely with hardware, firmware, and product teams to understand hardware dependencies, application requirements, and overall product goa
• ls.Develop thorough documentation for applications, APIs, and system integration poin
• ts.Conduct and participate in code reviews to ensure code quality and maintainability across the te
• am.Engage with stakeholders as needed to gather requirements, provide updates, and manage expectations regarding project timelines, deliverables, and potential challeng
• es.Drive continuous improvement by identifying and addressing inefficiencies in software and hardware interfac

es.
Requireme

• nts:Ability to travel up to
• 10�sign and develop embedded software solutions for various platforms, ensuring high performance and reliabil
• ity.Architect, code, and optimize embedded applications and systems using C, C , STL, Python, and shell script
• ing.Excellent in Linux programming, IPC, multi-threaded programming & Socket programm
• ing.Utilize object-oriented design principles (UML, design patterns) to build scalable and maintainable softw
• are.Debug and troubleshoot issues using tools such as GDB, Valgrind, Clang, TCP dump, and Wiresh
• ark.Proficiency or familiarity with one of the build systems such as CMake, Make or Ni
• nja.Work with embedded systems build environments (Buildroot, Yoc
• to).Awareness of Linux driver models, including board bring-up processes, Bootloaders and Device tree conce
• pts.Knowledge of communication protocols, including UART, I2C, SPI, TCP,
• UDP.Understanding of real-time operating systems (RTOS), such as FreeRTOS or Zephyr, and their integration within embedded syst
• ems.Ability to collaborate and write integration code on cloud technologies including REST APIs, MQTT, AWS, and SaaS for connected device soluti
• ons.Familiarity with version control systems like Git, SVN, or Mercurial for code management and version track
• ing.Experience setting up unit tests, integration tests, and system tests in the CI/CD pipel
• ine.Domain knowledge in Pro-AV/Broadcast or Imaging solutions is a p

lus.
Preferred experi

• ence:Multimedia frameworks (GStreamer, FFmpeg) to handle audio and video functionalities in embedded environments using protocols RTSP and RTP is prefe
• rred.Experience with NVIDIA GPU programming, including CUDA fundamentals, GPU memory management, and parallel computing optimizat
• ions.Familiarity with related technologies such as CUDA libraries (cuDNN), GPU-accelerated frameworks, and performance tuning tools like NVIDIA N

sight
Educa

• tion: Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related
• field.Minimum 8 years of hands-on experience in embedded systems develo