AI Research Engineer (Kernel & Inference Optimization)

📋 Description Design and deploy advanced model-serving architectures optimized for high throughput, low latency Develop inference pipelines capable of operating effectively across diverse environments, including Establish clear performance targets covering response latency, token generation speed, throughput Build and execute controlled inference benchmarks in simulated and production environments Create and maintain representative datasets and simulation scenarios for evaluating model Identify computational and memory bottlenecks across inference pipelines and implement solutions 🎯 Requirements Degree in Computer Science or a related technical field; a PhD in NLP, Machine Learning, or a Proven expertise in Metal Shading Language (MSL), including the ability to write custom compute Demonstrated experience with low-level kernel optimization and inference optimization on mobile or Track record of delivering measurable improvements in inference latency, throughput, and memory Deep understanding of modern model-serving architectures, inference engines, and optimization Strong experience writing GPU kernels for mobile devices such as smartphones. 🎁 Benefits Opportunity to work on advanced AI systems spanning model serving, inference optimization, mobile Remote-first working environment with an international team. Exposure to cutting-edge AI research and practical systems engineering challenges. Opportunity to contribute to performance-critical infrastructure where improvements can have a Collaborative environment combining research-driven experimentation with hands-on engineering. Opportunity to work with advanced model architectures including diffusion models, Vision