Principal Application Engineer
About This Role
We are seeking a Principal Application Engineer to drive deployment and integration of our ultra-low-power edge inference SoC within the U.S. Defense Industrial Base (DIB), including collaborations with Army, Navy, and Air Force research laboratories, broader DoW organizations, and federally funded research and development centers. This role sits at the intersection of silicon, embedded systems, and machine learning, with a focus on enabling real-world edge inference in highly constrained environments. Application areas include low-power sensing, image/video/signal processing, communications, and edge data reduction where power, size, and connectivity are limited.
Responsibilities
Serve as the primary technical interface for strategic DIB customers, including prime contractors, government laboratories, and system integrators.
Lead customer engagements spanning evaluation, system bring-up, integration, optimization, and deployment.
Drive technical discussions with senior engineers, architects, and program leadership within customer organizations.
Represent the company in technical reviews, demonstrations, integration activities, and field evaluations.
Guide customers in architecting ultra-low-power edge inference solutions around the SoC platform.
Advises on system-level tradeoffs involving performance, latency, memory footprint, power consumption, and sensor integration.
Support deployment and optimization of ML workloads for constrained edge environments.
Develop reference architectures, application notes, integration guides, and deployment best practices.
Lead debugging and root-cause analysis across hardware, firmware, SDK, model deployment, and system integration layers.
Perform hands-on bring-up and validation using lab instrumentation including oscilloscopes, logic analyzers, protocol analyzers, and power measurement tools.
Diagnose and resolve issues involving interfaces such as SPI, I2C, UART, GPIO, ADCs, and sensor pipelines.
Profile and optimize end-to-end system performance including latency, throughput, energy per inference, and memory utilization.
Influence translation of customer deployment challenges into actionable feedback for silicon, firmware, SDK, and software teams.
Identify product gaps, tooling limitations, and deployment friction points impacting adoption.
Help shape product roadmap priorities based on real-world customer usage and integration requirements.
Develop reusable methodologies and technical collateral to accelerate future customer engagements.
Mentor junior application engineers and help establish scalable customer support and debug methodologies.
Contribute to internal best practices for system integration, deployment workflows, and customer enablement.
Act as a senior escalation resource for complex technical issues and mission-critical deployments.
Support customer integration and deployment activities at customer sites, government labs, and field environments as needed.
Travel as required to support strategic engagements, bring-up activities, demonstrations, and deployment efforts.
Required Qualifications
U.S. citizenship required; ability to obtain and maintain a U.S. security clearance may be required.
Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, or related technical field.
Typically 8+ years of experience in applications engineering, embedded systems, semiconductor platforms, edge AI, or related technical roles.
Strong proficiency in C/C++ and embedded software development.
Strong Linux proficiency including command-line workflows, scripting, build systems, and development environments.
Experience with Python or similar scripting languages for automation, testing, or data analysis.
Deep experience with embedded systems, microcontrollers, device interfacing, and low-level system debugging.
Hands-on experience with hardware bring-up, instrumentation, and board-level debugging.
Demonstrated ability to debug and reason across hardware and software boundaries.
Strong technical communication and documentation skills, including creation of application notes, integration guides, and debug reports.
Willingness to travel to customer and government sites as needed.
Preferred Qualifications
Experience with TinyML, edge AI deployment, or ML inference optimization.
Familiarity with frameworks such as TensorFlow Lite, PyTorch, or related deployment environments.
Familiarity with signal processing, sensor fusion, or edge sensing applications.
Familiarity with semiconductor SoC platforms and low-power system design.
Experience with embedded toolchains, cross-compilation environments, and SDK development.
Familiarity with RF, communications, navigation, or distributed sensing systems.
Experience working with defense, aerospace, government R&D, or DIB organizations.
What Makes This Role Unique
Direct involvement in deploying cutting-edge edge AI silicon into mission-critical, resource-constrained environments.
Ownership of customer success from initial evaluation through operational integration.
Hands-on work across the full stack: sensors ? firmware ? ML inference ? system integration.
Opportunity to shape product direction through close interaction with advanced technical customers.
High-impact role spanning silicon, embedded systems, machine learning, and field deployment.
Significant autonomy and visibility across both engineering and customer organizations.
Salary Range
$120,000 - $180,000 / year