GPU Optimisation Specialist

Tasks: - Develop and implement methods for accelerating computations. - Configure containers for various accelerators (GPU, TPU, etc.). - Create strategies for balancing performance and quality. - Prepare specialized container images for specific architectures. - Design scalable systems for different computational protocols. - Adapt code to new versions of frameworks. - Integrate specialized hardware. Requirements: - Experience in optimizing large language models. - Deep knowledge of transformers and attention mechanisms. - Proficiency with accelerator tools and optimization techniques (CUDA, ROCm, etc.). - Experience with optimization frameworks (TensorRT, OpenVINO, Triton). - Understanding of containerization (Docker) and workload management (Kubernetes, Slurm). Nice-to-have: - Experience with distributed networks. - Participation in ML competitions. - Knowledge of modern accelerator architectures. - Work with specialized devices (FPGA, ASIC). Conditions: - Opportunity to transition to full-time employment with a share in revenue. - Bonuses tied to the real performance improvements you implement. Fully remote, flexible schedule.