Application Engineer – Low Power Edge Inference (DIB Focus)

About this Role
We are seeking an Application Engineer to support 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 service laboratories, as well as broader federally-funded defense contractors and research organizations.

This role sits at the intersection of silicon/emerging hardware, embedded systems, and machine learning, with a focus on enabling real-world edge inference in highly constrained environments. Typical application areas include low-power sensing, image/video/signal processing, communications, and edge data reduction where power, size, and connectivity are limited.

You will work directly with customers to bring up systems, integrate models, and debug issues across hardware and software boundaries. This is an entry-level role with significant on-the-job training. Strong fundamentals, hands-on experience, self-motivation and learning agility are more important than prior domain specialization.

Responsibilities:
Customer Enablement

• Serve as a technical interface between internal engineering teams and DIB customers (prime contractors, government labs, and system integrators)
• Support customer evaluation, system bring-up, and integration of the SoC into system platforms
• Develop reference designs, application notes, and integration guides for mission-driven use cases
• Troubleshoot system-level issues spanning hardware, firmware, and ML inference pipelines

Technical Integration

• Assist customers in deploying and optimizing ML models for ultra-low-power edge inference
• Support sensor integration (e.g., audio, RF, vision) and data pipelines into the SoC
• Profile and improve system performance (latency, energy per inference, memory usage, accuracy)
• Work with SDKs, toolchains, and embedded environments to enable rapid prototyping and deployment

Debug & Bring-Up

• Perform hands-on debugging of hardware/software systems using lab instrumentation
• Diagnose issues across interfaces (e.g., SPI, I2C, GPIO) and system components
• Support board bring-up and validation in both internal labs and customer environments

Internal Feedback Loop

• Translate customer requirements into actionable feedback for silicon, firmware, and software teams
• Identify gaps in tooling, documentation, or product capabilities impacting adoption
• Support validation of new features in real-world deployment scenarios

Field Engagement

• Support demos, pilots, and integration efforts at customer and government lab sites
• Travel as needed to support on-site bring-up, debugging, and deployment

Required Qualifications:

• Bachelor’s degree or higher in Electrical Engineering, Computer Engineering, Computer Science, or related field
• Proficiency in C/C++ demonstrated through coursework, projects, or internships
• Experience with embedded or low-level systems (e.g., microcontrollers, device interfacing, or systems programming)
• Familiarity with Linux development environments (command line, build tools, scripting)
• Familiarity with Python or similar scripting languages
• Hands-on experience with hardware debugging and bring-up (e.g., oscilloscopes, logic analyzers, multimeters) through coursework or projects
• Ability to debug and reason across hardware and software boundaries
• Strong problem-solving skills and ability to learn quickly in unfamiliar technical domains
• Clear communication skills with the ability to explain technical concepts to diverse audiences
• Ability to produce clear, concise technical documentation (e.g., integration guides, application notes, and debugging reports)
• Willingness to travel to customer and government lab sites as needed
• U.S. citizenship required; ability to obtain and maintain a U.S. security clearance may be required

Preferred Qualifications:

• Exposure to machine learning, TinyML, or model deployment workflows (e.g., TensorFlow Lite, PyTorch)
• Familiarity with signal processing concepts or sensor data analysis
• Experience with embedded toolchains, build systems, or cross-compilation
• Familiarity with common hardware interfaces (SPI, I2C, UART, ADCs)
• Experience with version control systems (e.g., Git)
• Internship or project experience in semiconductors, robotics, embedded systems, or related fields
• Familiarity with defense or government R&D environments

What Makes This Role Unique:

• Direct involvement in deploying cutting-edge edge AI silicon into real-world, resource-constrained systems
• Hands-on work across the full stack: sensors ? firmware ? ML inference ? system integration
• Exposure to mission-critical applications in challenging operating environments
• Opportunity to develop into a highly cross-functional engineer spanning hardware, software, and ML

Work Environment:

• Combination of lab-based engineering, customer interaction, and field support
• Close collaboration with silicon design, firmware, and ML software teams
• Fast-paced, hands-on environment focused on delivering deployable solutions, not just prototypes

Salary Range: $120,000 - $180,000 / year