Lead Flight Software Engineer - Algorithms, Embedded C/C++,

Tittle : Lead Flight Software Engineer - Algorithms, Embedded C/C++,
Work Location: Onsite in Azusa, CA
Duration: 2 months
Terms: W2 Contract
Work Authorization: US Citizen

Key Skills: Algorithms, Embedded C/C++, RTOS, Flight Software, FPGA/CPU/GPU, Hardware/Software Integration

Position Summary:

• As an Algorithm Software Engineer Lead, you will support our Flight Software Department.
• As a member of the Flight Software Department, you’ll get to implement flight software solutions.

• Bachelor's degree in a STEM discipline with 12 years of relevant experience;
• OR a Master's degree in a STEM discipline with 10 years of relevant experience;
• OR a PhD in a STEM discipline with 8 years of relevant experience.
• Ability to translate MARs into flight software code.
• Strong math proficiency for algorithm development and implementation.
• Proficiency in software development and execution for embedded/flight systems.
• Understanding of kernel-level concepts (OS, kernel, low-level software).
• Experience working in flight environments (real-time operating systems, flight software constraints).
• Experience integrating software into third-party platforms.
• Strong background in embedded systems development.
• Experience with flight hardware and hardware–software integration.
• Hands-on experience implementing algorithms in embedded/flight code.
• Familiarity with Agile project management practices.

• Active DoD Secret clearance is preferred, not mandatory.
• Experience optimizing intra-SoC distributed processing across integrated FPGA, CPU, and GPU components.
• Expertise with NVIDIA Orin Jetson platforms for high-performance, real-time processing.
• Experience with Polarfire FPGAs and their integration into embedded systems.
• Proven ability to design and implement high-bandwidth (20 Gbps) real-time processing solutions.
• Demonstrated skill in minimizing processing latency in heterogeneous compute architectures.
• Strong background in mapping and fitting complex algorithms to fixed hardware configurations.
• Knowledge of hardware–software co-design principles for embedded/compute-intensive systems.