What You’ll Do

• Own, define and lead the end-to-end perception architecture—from cloud training to deployment-ready model variants for automotive-grade SoCs (e.g., Qualcomm Snapdragon Ride, NVIDIA Orin, or similar).
• Drive a deployment-first approach across architecture decisions, including quantization, latency targets, and memory constraints.
• Turn state-of-the-art perception research into reliable, scalable production pipelines (cloud + edge model variants).
• Guide BEV / multi-camera perception focused on road infrastructure (lanes, boundaries, signs, traffic lights, road surface attributes).
• Define evaluation and validation standards, including hardware-aware metrics (latency vs accuracy trade-offs, memory footprint, throughput on reference hardware).
• Partner closely with research, simulation, product, and customer/partner teams to ensure outputs are usable by downstream systems and meet real deployment needs.
• Remain deeply hands-on in architecture reviews, model design, technical investigations, debugging critical issues, and evaluation of new approaches and engineering execution. This role requires active technical contribution, not only leadership.
• Help build and scale a high-performing perception engineering team from the ground up and establishing engineering standards, development processes, and a strong culture of technical excellence.
• Partner closely with customers to understand real-world challenges and translate them into scalable solutions.

What You’ll Do

• Own, define and lead the end-to-end perception architecture—from cloud training to deployment-ready model variants for automotive-grade SoCs (e.g., Qualcomm Snapdragon Ride, NVIDIA Orin, or similar).
• Drive a deployment-first approach across architecture decisions, including quantization, latency targets, and memory constraints.
• Turn state-of-the-art perception research into reliable, scalable production pipelines (cloud + edge model variants).
• Guide BEV / multi-camera perception focused on road infrastructure (lanes, boundaries, signs, traffic lights, road surface attributes).
• Define evaluation and validation standards, including hardware-aware metrics (latency vs accuracy trade-offs, memory footprint, throughput on reference hardware).
• Partner closely with research, simulation, product, and customer/partner teams to ensure outputs are usable by downstream systems and meet real deployment needs.
• Remain deeply hands-on in architecture reviews, model design, technical investigations, debugging critical issues, and evaluation of new approaches and engineering execution. This role requires active technical contribution, not only leadership.
• Help build and scale a high-performing perception engineering team from the ground up and establishing engineering standards, development processes, and a strong culture of technical excellence.
• Partner closely with customers to understand real-world challenges and translate them into scalable solutions.