AI Computing Architect

We are seeking an outstanding Performance Analysis Architect to help analyse and develop the next generation of architectures that accelerate AI and high-performance computing applications.

As an AI Computing Architect, you will be responsible for developing innovative architectures to extend the state of the art in deep learning performance and efficiency. You will also analyse performance, cost and power trade-offs by developing analytical models, simulators and test suites.

Key responsibilities include:

• Developing innovative architectures to extend the state of the art in deep learning performance and efficiency
• Analysing performance, cost and power trade-offs by developing analytical models, simulators and test suites
• Understanding and analysing the interplay of hardware and software architectures on future algorithms, programming models and applications
• Prototyping key deep learning and data analytics algorithms and applications
• Actively collaborating with software, product and research teams to guide the direction of deep-learning

Requirements include:

• BS or higher degree in a relevant technical field (CS, EE, CE, Math, etc.) with 3+ years of work experience
• Strong programming skills in Python, C, C++
• Strong background in computer architecture
• Experience with performance modelling, architecture simulation, profiling, and analysis
• Strong foundation in machine learning and deep learning

Nice-to-have skills include:

• Experience with GPU Computing and parallel programming models such as CUDA and OpenCL
• Background with the architecture of or workload analysis on other deep learning accelerators
• Experience with deep neural network training, inference and optimisation in leading frameworks (e.g. PyTorch, TensorFlow, TensorRT)
• Experience with open-source AI compilers (OpenAI Triton, MLIR, TVM, XLA, etc.)