Job Description:
As a Senior AI Research Engineer, you will play a critical role in pushing the boundaries of desktop and on-device inference and fine-tuning performance for next-generation SLM/LLMs. You will extend the inference framework to support inference and fine-tuning for Language models with a strong focus on mobile and integrated GPU acceleration (Vulkan).
Responsibilities:
• Implement and optimize custom inference and fine-tuning kernels for small and large language models across multiple hardware backends.
• Implement and optimize full and LoRA fine-tuning for small and large language models across multiple hardware backends.
• Design and extend datatype and precision support (int, float, mixed precision, ternary QTypes, etc.).
• Design, customize, and optimize Vulkan compute shaders for quantized operators and fine-tuning workflows.
• Investigate and resolve GPU acceleration issues on Vulkan and integrated/mobile GPUs.
• Architect and prepare support for advanced quantization techniques to improve efficiency and memory usage.
• Debug and optimize GPU operators (e.g., int8, fp16, fp4, ternary).
• Integrate and validate quantization workflows for training and inference.
• Conduct evaluation and benchmarking (e.g., perplexity testing, fine-tuned adapter performance).
• Conduct GPU testing across desktop and mobile devices.
• Collaborate with research and engineering teams to prototype, benchmark, and scale new model optimization methods.
• Deliver production-grade, efficient language model deployment for mobile and edge use cases.
• Work closely with cross-functional teams to integrate optimized serving and inference frameworks into production pipelines designed for edge and on-device applications.
• Define clear success metrics such as improved real-world performance, low error rates, robust scalability, optimal memory usage and ensure continuous monitoring and iterative refinements for sustained improvements.
