Senior Engineer -Machine Learning Tools

Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience. 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc. Master's/Bachelor's degree in computer science or equivalent. 6+ years of relevant work experience in software development. Strong understanding of Generative AI models - LLM, LVM, LMMs and building blocks (self-attention, cross attention, kv caching etc.) Floating-point, Fixed-point representations and Quantization concepts. Experience with optimizing algorithms for AI hardware accelerators (like CPU/GPU/NPU). Strong in C/C++ programming, Design Patterns and OS concepts. Ability to collaborate across a globally diverse team and multiple interests. Strong understanding of SIMD processor architecture and system design. Proficiency in object-oriented software development and familiarity Familiarity with Linux and Windows environment Strong background in kernel development for SIMD architectures. Familiarity with frameworks like llama.cpp, MLX, and MLC is a plus. Good knowledge of PyTorch, TFLite, and ONNX Runtime is preferred. Experience with parallel computing systems and languages like OpenCL and CUDA is a plus. As an AI inferencing expert, you'll push the limits of performance from large models. Your mastery in deploying large C/C++ software stacks using best practices will be essential. You'll stay on the cutting edge of GenAI advancements, understanding LLMs/Transformers and the nuances of edge-based GenAI deployment. Most importantly, your passion for the role of edge in AI's evolution will be your driving force.