Embedded Systems Engineer (Space & High-Réilyability Systems)Job Summary
We are seeking an experienced Embedded Systems Engineer to evaluate and optimize the deployment of advanced analytical workflows on spaceflight and other resource-constrained computing platforms. This role will assess the feasibility of running computationally intensive algorithms in environments with strict limitations on processing power, memory, energy consumption, and system reliability.
The ideal candidate will have experience with embedded systems, FPGA development, and high-reliability computing environments such as aerospace, space, defense, or avionics applications. This individual will collaborate closely with software, data science, and engineering teams to identify performance constraints, recommend optimization strategies, and support technology maturation efforts.
Key Responsibilities
- Evaluate and profile analytical software workflows on embedded and onboard processing architectures.
- Measure and analyze system performance, including:
- Processing throughput
- Memory utilization
- Latency
- Power consumption
- Identify computational bottlenecks and performance limitations across processing pipelines.
- Develop hardware/software partitioning strategies, including CPU and FPGA-based acceleration approaches.
- Collaborate with software and algorithm development teams to evaluate optimization opportunities, including:
- Model compression
- Fixed-point conversion
- Reduced-order computational techniques
- Assess radiation-related impacts and mitigation strategies for space-based platforms, including fault tolerance and system resiliency considerations.
- Contribute to embedded system and onboard processing architecture design, including data flow, interfaces, and secure communications pathways.
- Create technical trade studies, performance assessments, and technology roadmaps to support engineering decisions and future program execution.
- Support hardware-in-the-loop testing, validation activities, and transition planning for operational deployment.
- Develop confidence metrics and technical documentation to support system performance assessments and operational decision-making.
Required Qualifications
- Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related technical field.
- 5+ years of experience developing or evaluating embedded systems in aerospace, defense, avionics, space, or other high-reliability environments.
- Strong programming experience in:
- Experience profiling, optimizing, and troubleshooting computationally intensive applications.
- Demonstrated experience with radiation-tolerant, radiation-hardened, or other mission-critical processing platforms.
- Hands-on FPGA development experience using:
- VHDL and/or Verilog
- High-Level Synthesis (HLS) toolchains
- Knowledge of:
- Real-time systems
- SWaP (Size, Weight, and Power) constraints
- Deterministic memory management
- Latency and performance analysis
- Experience creating technical evaluations, trade studies, and engineering recommendations supported by measurable data.
- Ability to obtain and maintain a U.S. Government security clearance.
Preferred Qualifications
- Experience supporting spaceflight hardware or systems that have completed qualification, testing, or deployment activities.
- Experience deploying machine learning or AI inference models on embedded platforms, FPGA targets, or edge computing devices.
- Familiarity with spacecraft avionics architectures, onboard data handling systems, and flight software development practices.
- Knowledge of industry standards such as DO-178C, NASA software standards, or comparable aerospace development frameworks.
- Experience implementing embedded cybersecurity, cryptographic technologies, or secure key management solutions.
- Prior experience supporting government-funded research and development programs, including technology transition and roadmap planning efforts.
Work Environment
- Full-time position.
- Collaboration with multidisciplinary engineering, software, and data science teams.
- May require eligibility for government or defense-related programs and security clearance sponsorship.
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