Senior Edge Architect

We are seeking a Senior Edge Architect to join an autonomy program for a global heavy-equipment manufacturer with more than a decade of experience running autonomous machines in the field, now building fleets of autonomous machines that operate unsupervised at customer sites. In this role, you will work embedded in the client’s program from Europe, alongside US-based perception architects and the client’s edge team, owning the architecture of the on-machine compute platform, from NVIDIA Thor-class hardware and its I/O through the Linux BSP and ROS 2 middleware to the services that perception, data collection and autonomy run on.

Responsibilities

• Edge Hardware Architecture: Define the next-generation kit around NVIDIA Thor-class modules (Jetson AGX Thor and IGX Thor), covering sensor I/O, camera and network interfaces, storage, power and enclosure for dusty, high-vibration conditions and terabyte-scale data per machine.
• Low-Level Software Stack: Own the NVIDIA Linux BSP, kernel and drivers, device tree, boot and over-the-air updates.
• Middleware & Common Driver Layer: Design the middleware on ROS 2 (Jazzy) and Isaac ROS, lead the migration to ROS 2, and build a common driver and service layer so cameras, LiDARs, radars, GNSS and IMUs can be added or removed without redesign.
• Time Sync, Logging & Onboard Inference: Set up precise time sync across all sensors (GNSS/UTC, PPS, PTP), high-throughput logging that never drops data, and onboard GPU inference (detection, segmentation, fusion) with event-triggered capture within compute and thermal limits.
• Fleet Operations at Scale: Build in remote enable/disable, health and diagnostics reporting, and secure, encrypted data handling as the data-collection fleet scales to 500+ machines, making kit health visible remotely without engineers going on site.
• Architecture Decisions & Roadmap: Decide with the robotics team whether data logging and autonomy compute share hardware, and co-author the 2027 program charter and roadmap with the client, turning architecture into working software quickly alongside AI coding agents.

Requirements

• 8+ years of experience in embedded or edge systems for robotics, autonomous vehicles or industrial machines.
• NVIDIA Edge Hardware: Direct, hands-on experience with NVIDIA Jetson or IGX platforms, ideally the Thor generation.
• Hardware & I/O Integration: Experience with camera interfaces (GMSL, MIPI CSI), automotive Ethernet, CAN and storage throughput.
• Linux BSP & Drivers: Development and customization of the Linux BSP, kernel and NVIDIA drivers (JetPack, L4T), in C++.
• NVIDIA Software Ecosystem: Practical experience with CUDA, TensorRT, DeepStream and Isaac ROS.
• Production ROS 2: Building nodes, DDS tuning, rosbag2 or MCAP logging, and keeping performance up under high sensor load.
• Time Sync & Multi-Sensor Integration: Proven experience integrating and synchronizing cameras, LiDAR, radar and GNSS/IMU (PTP/PPS).

Nice to have

• Ruggedized Deployments: Experience with off-road, construction, mining or agriculture machines.
• Sensor Calibration: Calibration expertise, including online monitoring of calibration health.
• Fleet-Scale Edge Data: Edge data reduction, compression and encryption, plus device management, OTA and remote diagnostics across hundreds to thousands of units.
• Functional Safety: Safety-related embedded development under ISO 26262 or ISO 13849.
• Travel Readiness: Availability for pre-approved trips to client sites.

We offer

• Opportunity to work on bleeding-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package - medical insurance, sports
• Corporate social events
• Professional development opportunities
• Well-equipped office

About Us Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.