Job Description

Building and optimizing inference pipelines for large-scale model serving (LLMs and beyond)
Working with frameworks like PyTorch, TensorRT, and vLLM to deploy models efficiently
Implementing and optimizing ML models using techniques such as quantization (INT8/FP8), kernel fusion, and efficient batching
Optimizing and implementing core ML operators (e.g., GEMMs, convolutions, activations, ...)
Investigating and resolving issues through system-level debugging and performance analysis
Defining and applying practices for testing, deployment, and scaling AI systems

BSc/MSc in Computer Science, Engineering, Mathematics, or related discipline
Strong programming skills in C/C++ or Python in Linux environments using common development tools
Solid knowledge of computer architecture, system software, data structures
Hands-on experience implementing algorithms in high-level languages