Graphcore is an AI infrastructure and hardware company.
<p><strong>Salary Range: PLN 260,400 - 352,200<br></strong></p> <p><strong>Subject to alignment to the responsibilities and duties of the role.</strong></p> <h2><strong>About Graphcore </strong></h2> <p>At Graphcore, we’re building the future of AI compute.</p> <p>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.</p> <p>As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.</p> <p>To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.</p> <p>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.</p> <p><strong><span data-contrast="none">Job Summary</span></strong><strong><span data-contrast="none"> </span></strong><span data-ccp-props="{}"> </span></p> <p>As a Senior Software Engineer, you’ll build high-performance AI compute libraries for next-generation AI hardware, working on linear algebra, tensor operations, numerical correctness, and low-level performance optimisation.</p> <p><strong><span data-contrast="auto">The Team</span></strong><span data-ccp-props="{}"> </span></p> <p><span data-contrast="none">This is an exciting opportunity to join an expanding team at Graphcore. Our ML Kernels & Runtime team are responsible for delivering high performance compute library to help customers gain the maximum performance from AI hardware.</span><span data-ccp-props="{}"> </span></p> <p><strong><span data-contrast="auto">Responsibilities and Duties</span></strong><span data-ccp-props="{}"> </span></p> <ul> <li data-leveltext="" data-font="Symbol" data-listid="3" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"multilevel"}" data-aria-posinset="1" data-aria-level="1"><span data-contrast="none"><span data-ccp-parastyle="Normal (Web)">Design and implement kernels for linear algebra and tensor ops (GEMM, batched GEMM, convolutions, reductions, elementwise and fused operations) in C++</span></span><span data-ccp-props="{"134233117":false,"134233118":false,"335559738":0,"335559739":0}"> </span></li> </ul> <ul> <li data-leveltext="" data-font="Symbol" data-listid="3" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"multilevel"}" data-aria-posinset="2" data-aria-level="1"><span data-contrast="none"><span data-ccp-parastyle="Normal (Web)">Own performance and correctness - add microbenchmarks, regression tests, </span><span data-ccp-parastyle="Normal (Web)">numerics</span><span data-ccp-parastyle="Normal (Web)"> validation</span></span><span data-ccp-props="{"134233117":false,"134233118":false,"335559738":0,"335559739":0}"> </span></li> </ul> <ul> <li data-leveltext="" data-font="Symbol" data-listid="3" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"multilevel"}" data-aria-posinset="3" data-aria-level="1"><span data-contrast="none"><span data-ccp-parastyle="Normal (Web)">Profile and optimise across for next generation of AI hardware - threading, cache locality, memory layout, and kernel launch efficiency.</span></span><span data-ccp-props="{"134233117":false,"134233118":false,"335559738":0,"335559739":0}"> </span></li> </ul> <ul> <li data-leveltext="" data-font="Symbol" data-listid="3" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"multilevel"}" data-aria-posinset="4" data-aria-level="1"><span data-contrast="none"><span data-ccp-parastyle="Normal (Web)">Debug issues, resolve bugs and </span><span data-ccp-parastyle="Normal (Web)">generally improve</span><span data-ccp-parastyle="Normal (Web)"> the quality and functionality of the product</span></span><span data-ccp-props="{"134233117":false,"134233118":false,"335559738":0,"335559739":0}"> </span></li> </ul> <ul> <li data-leveltext="" data-font="Symbol" data-listid="3" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"multilevel"}" data-aria-posinset="5" data-aria-level="1"><span data-contrast="none"><span data-ccp-parastyle="Normal (Web)">Actively engage in and support Agile ways of working within the team</span></span><span data-ccp-props="{"134233117":false,"134233118":false,"335559738":0,"335559739":0}"> </span></li> <li data-leveltext="" data-font="Symbol" data-listid="3" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"multilevel"}" data-aria-posinset="6" data-aria-level="1"><span data-contrast="none"><span data-ccp-parastyle="Normal (Web)">Mentor colleagues within the team, sharing knowledge and providing guidance where appropriate</span></span><span data-ccp-props="{"134233117":false,"134233118":false,"335559738":0,"335559739":0}"> </span></li> </ul> <p><strong><span data-contrast="none">Candidate Profile </span></strong> <br><span data-ccp-props="{}"> </span></p> <p><strong><span data-contrast="auto">Essential</span></strong><span data-ccp-props="{}"> </span></p> <ul> <li data-leveltext="" data-font="Symbol" data-listid="1" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777