Senior Software Engineer - ML Kernels & Runtime

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Salary Range: PLN 260,400 - 352,200 Subject to alignment to the responsibilities and duties of the role. About Graphcore At Graphcore, we're building the future of AI compute. We're a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale. As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem. To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world. We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence. Job Summary As a Senior Software Engineer, you will be responsible for development of new and support existing kernels for linear algebra operations on a new generation of AI hardware. The Team This is an exciting opportunity to join an expanding team at Graphcore. Kernel Engineering team is responsible for delivering high performance compute library to help customers gain the maximum performance from AI hardware. Responsibilities and Duties Design and implement kernels for linear algebra and tensor ops (GEMM, batched GEMM, convolutions, reductions, elementwise and fused operations) in C++ Own performance and correctness - add microbenchmarks, regression tests, numerics validation Profile and optimise across for next generation of AI hardware - threading, cache locality, memory layout, and kernel launch efficiency. Debug issues, resolve bugs and generally improve the quality and functionality of the product Actively engage in and support Agile ways of working within the team Mentor colleagues within the team, sharing knowledge and providing guidance where appropriate Candidate Profile Essential Excellent programming and scripting skills using C++ and Python Understanding of processor architectures and profiling on Linux Possess excellent written and oral communication skills, good work ethics, high sense of team-work Love to produce quality work and be a team player Desirable Strong command of algorithmic performance - vectorisation, memory hierarchy, threading, lock-free patterns Hands-on with at least one BLAS/DNN stack and able to read/extend kernels Comfort with CPU micro-optimisations and numerical stability/trade-offs across FP32/FP16/BF16/FP8 Experience integrating native code into PyTorch or similar (custom ops, extensions, dispatch keys) ABI/API stability and packaging for Linux system ( manylinux , wheels)

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