Senior Field Application Engineer (FAE) - MPU & DNPU – Robotics/Drones

AI is rapidly moving beyond research labs and into the real world—powering advancements in vehicles, factories, hospitals, homes, drones and everyday devices. NXP’s Global Sales organization is the force that transforms our intelligent edge vision into meaningful market impact. We operate on the front lines of innovation, delivering real‑world AI, secure edge intelligence, and breakthrough technologies to the customers shaping tomorrow’s world.

As a strategic partner at the intersection of customer ambition and NXP capability, our global sales team drives alignment, opens new markets, and builds the relationships that lead to design wins and revenue growth.

As part of the evolution of the European Microprocessors (MPUs) and Discrete Neural Processors Units (DNPUs) Field Application Engineering organization, we are looking for a senior FAE to support our solutions for key customers in EMEA with a focus on the robotics segment and more specifically drones.

In this role, working closely with Sales and Key Account Managers, you will act as the primary technical interface to customer engineering teams, supporting system architects and developers in defining and deploying next-generation systems.

Responsibilities

• Provide technical leadership to sales teams and customers covering edge-compute architecture, processor selection, bring-up, and software stack integration for NXP MPU and DNPU processors targeting robotics platforms.

• Partner with customers on the design of companion computers, central compute, vision/perception subsystems, and HMI nodes — from silicon selection through Linux board bring-up, kernel/driver enablement, and system performance tuning.

• Design support and lab troubleshooting through schematic reviews, bench bring-up, debugging, and root-cause analysis across hardware, kernel, drivers, and middleware.

• Enable customer AI, vision, and sensor-fusion workloads on NXP processors and integrated NPUs, helping customers move models from training frameworks to optimized on-device inference for perception, navigation, and HMI use cases.

Job Qualifications

• Master’s degree in Electrical Engineering, Computer Engineering or Computer Science

• 10+ years in embedded systems development or applications support of MPU / SoC-based platforms running embedded Linux, with demonstrated technical leadership.

• Strong embedded Linux experience across the full stack: bootloader (u-boot), kernel and device drivers, device tree, Yocto / build system, and user-space integration.

• Working knowledge of Python or scripting for tooling and automation.

• Hands-on experience with ARM Cortex-A class application processors and heterogeneous compute architectures pairing application cores with real-time microcontroller cores.

• Working knowledge of high-speed application-processor interfaces and how to design around them: LPDDR, PCIe, USB 3.x, MIPI-CSI / MIPI-DSI, Gigabit / Multi-Gigabit Ethernet, SDIO / eMMC, and QSPI.

• Excellent verbal and written communication for both technical and non-technical stakeholders.

• Willingness to travel

• Fluent English required

Specialty and bonus skills

• Hands-on experience enabling AI / ML workloads on edge processors and integrated NPUs, including model conversion and optimization from common training frameworks to on-device inference for robotics perception.

• Familiarity with robotics middleware and stacks: Rust, ROS / ROS 2, DDS, real-time Linux (PREEMPT_RT), and common SLAM, navigation, and motion-planning frameworks.

• Working knowledge of platform security: TrustZone, secure boot, OP-TEE, integrated secure enclaves, and secure-element integration for authenticated robotics endpoints.

• Familiarity with power-management subsystems for application processors (PMIC integration, DVFS, multi-rail / thermal management) and battery-powered system architectures.

• Working knowledge of functional safety (ISO 26262, IEC 61508 / SIL 2–3) and cybersecurity (ISO 21434, IEC 62443) standards relevant to industrial and automotive edge-compute systems.

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