Senior DL Software Engineer, Model Optimization and Edge Deployment - Autonomous Vehicles

Job description

NVIDIA is at the forefront of the AI revolution, specifically in the constantly evolving field of Embodied AI. We are seeking a high-caliber Deep Learning Engineer to bridge the gap between cutting-edge multimodal architectures and real-time robotic execution for autonomous vehicles. In this role, you will design and implement SOTA algorithms to make LLM/VLM fast, lean, and reliable enough to power an end-to-end driving stack. You won’t just be "running" models; you will be re-architecting them for the edge, ensuring that models capable of complex scene reasoning can operate within the strict latency and safety constraints of an AV compute platform. What You’ll Be Doing: Develop SOTA model optimization techniques, such as speculative decoding with block diffusion, KV cache streaming, and Prefill–Decode separation, etc. to boost E2E model performance for production deployments. Implement advanced compression techniques including Quantization (FP4/FP8), pruning, and knowledge distillation to minimize model footprints without compromising safety-critical accuracy. Design high-performance optimization strategies for inference, including automated model sharding (tensor/sequence paralle...