LLM Algorithmic Optimization Engineer - Intern
Core
Research and optimize Large Language Models (LLMs) and multimodal models for efficient inference and deployment in automotive digital cockpits and autonomous driving systems.
Role type
Intern, LLM Algorithmic Optimization Engineer
Builds
Optimized LLM inference pipelines for vehicle digital cockpits and advanced driving (AD) domains
Domain
Automotive AI, Large Language Models, Edge Computing
Deliverable
production ML models
Required skills
GPU/NPU architecture optimization, LLM and VLM architectures, Transformer algorithms, Python, C/C++, PyTorch, ONNX, distributed computing debugging
Preferred skills
Microkernel architecture, Linux kernel, hypervisor, middleware, application framework, high-impact publication records
Technologies
PyTorch, ONNX, GPUs, NPU
Responsibilities
Conduct research and apply cutting-edge technologies to optimize LLMs and multimodal models; Focus on model optimization from a systems perspective for efficient deployment in vehicle digital cockpits and AD domain; Collaborate with cross-functional teams to integrate optimized models into real-world automotive applications; Contribute to the entire pipeline from research, development, and testing through to deployment on hardware including GPUs and distributed systems
Seniority
Intern