Senior/Staff Software Engineer - Machine Learning & System Optimization

Allocate and distribute system resources (CPU/GPU/interconnect) to various models and inference engines running on the robot.

Spearhead cross-cutting initiatives that allow for better compute utilization through sharing/fusing models and better scheduling strategies.

Optimize large-scale models (Multi-Modal Sensor Fusion models, LLMs, VLMs) using advanced quantization (PTQ, QAT), pruning, mixed-precision inference frameworks, and parameter-efficient fine-tuning (LoRA, QLoRA).

Architect and implement model conversion and compilation pipelines using TensorRT for edge deployment.

Write production-level, low-latency, and memory-safe C++ and CUDA code for real-time inference on vehicle systems.

Prior experience in high-performance robotics applications such as AV/drones/robots.

Familiarity with SOTA autonomous driving perception algorithms (temporal 3D object detection, BEV, 3D Occupancy Networks) and multi-modal sensor processing (Vision, LiDAR, Radar).