Graphcore is an AI infrastructure and hardware company.
<h3 class="PDq2pG_selectionAnchorContainer" data-start="135" data-end="148"><strong>About the job</strong></h3> <p data-start="150" data-end="235">Build the compute kernels that make next-generation AI hardware perform at its limit.</p> <p data-start="237" data-end="440">As a Senior Software Engineer, you will create high-performance AI compute libraries for Graphcore’s next-generation hardware. Your work will sit close to the hardware, where every design choice matters.</p> <p data-start="442" data-end="665">You will own kernels for linear algebra and tensor operations, including GEMM, convolutions, reductions and fused operations. You will improve performance, correctness and numerical reliability across critical AI workloads.</p> <p data-start="667" data-end="842">This role is for engineers who enjoy hard performance problems and care deeply about quality. You will help shape software that enables customers to get more from AI hardware.</p> <h3 data-start="844" data-end="864"><strong>The team and culture</strong></h3> <p data-start="866" data-end="1041">You will join the ML Kernels and Runtime team, an expanding group focused on high-performance compute libraries. The team works close to the hardware and close to the product.</p> <p data-start="1043" data-end="1229">Work happens through clear ownership, practical decision-making and fast technical feedback. Engineers profile, test, debug and improve the product with accountability for real outcomes.</p> <p data-start="1231" data-end="1380">You will be expected to speak up, share knowledge and help others raise the bar. Mentoring, technical judgement and all-round leadership matter here</p> <h3><strong><span data-contrast="auto">Responsibilities and Duties</span></strong><span data-ccp-props="{}"> </span></h3> <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":"","469777815":"multilevel"}" data-aria-posinset="1" data-aria-level="1"><span data-contrast="none"