{"id":17046,"url":"https://alion.io/job/cerebras-kernel-engineer-new-grad","title":"Kernel Engineer - New Grad","company":{"id":31,"name":"Cerebras Systems","domain":"cerebras.ai","url":"https://alion.io/company/cerebras-systems","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":76,"open_postings":25,"ghost_share":0,"stale_share":0.76,"repost_share":0,"time_to_fill_p50_days":86,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Hardware","role_family":"Hardware","seniority":"junior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Sunnyvale, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":120000,"max_usd":234000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":468},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"C++","optional":false},{"name":"Cerebras","optional":false},{"name":"Edge AI","optional":false},{"name":"HPC","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenAI","optional":false},{"name":"Python","optional":false},{"name":"Assembly","optional":true},{"name":"CUDA","optional":true},{"name":"CUDA Toolkit","optional":true},{"name":"OpenCL","optional":true},{"name":"PyTorch","optional":true},{"name":"PyTorch C++","optional":true},{"name":"TensorFlow","optional":true},{"name":"TensorFlow C++","optional":true}],"status":"live","first_seen_at":"2026-07-23T19:33:16Z","employer_posted_date":"2026-07-23","last_verified_at":"2026-10-17T09:14:57Z","board_verified":true,"closed_at":null,"days_open":85,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":85},"description":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\nAbout the Role\nAs a Kernel Engineer at Cerebras, you will develop high-performance software at the intersection of hardware and software for cutting-edge artificial intelligence and high-performance computing workloads.\nYou will help implement, optimize, and validate machine learning and linear algebra operations for the Cerebras Wafer-Scale Engine, our custom massively parallel processor architecture. Working alongside experienced kernel, compiler, performance, and hardware engineers, you will learn how algorithms are mapped to specialized hardware and contribute to software that maximizes compute utilization and system performance.\nYou will be part of a team responsible for the design, development, performance tuning, and validation of foundational ML and HPC kernels. This is an excellent opportunity for a new graduate who is interested in computer architecture, parallel programming, low-level software, and machine learning systems.\nResponsibilities\nHelp design and implement machine learning and linear algebra kernels for the Cerebras Wafer-Scale Engine.\n\nDevelop and debug high-performance kernel routines using low-level programming techniques and the Cerebras Software Language, a custom C-like language.\n\nApply parallel programming algorithms to map computational workloads efficiently onto the Cerebras architecture.\n\nUse mathematical analysis, performance data, and profiling tools to evaluate kernel behavior and inform design decisions.\n\nIdentify and investigate correctness, performance, and hardware utilization issues.\n\nDevelop unit tests and system-level validation methodologies to verify the functionality and performance of kernel libraries.\n\nCollaborate with kernel, compiler, performance, and hardware engineers to improve software and system performance.\n\nStudy emerging machine learning workloads and contribute to the evolution of the kernel library.\n\nParticipate in code reviews, technical discussions, and software development processes.\n\nBuild an understanding of the Cerebras architecture, instruction set, memory system, and communication model.\n\nMinimum Skills & Qualifications\nBachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a related field.\n\nStrong programming fundamentals in C++ and familiarity with Python.\n\nUnderstanding of foundational computer architecture concepts such as processors, memory hierarchies, instruction execution, or data movement.\n\nKnowledge of data structures, algorithms, and software development fundamentals.\n\nExperience debugging software through coursework, internships, research, co-op placements, or technical projects.\n\nStrong analytical and problem-solving skills.\n\nInterest in low-level software, parallel computing, performance optimization, or hardware/software co-design.\n\nAbility to learn unfamiliar systems and collaborate effectively within a technical team.\n\nPreferred Skills & Qualifications\nResearch, internships, or projects involving kernel development, compilers, computer architecture, HPC, or systems programming.\n\nFamiliarity with parallel algorithms, multithreaded programming, or distributed memory systems.\n\nExposure to programming accelerators such as GPUs, FPGAs, or other specialized processors.\n\nExperience with low-level programming, assembly language, CUDA, OpenCL, or a domain-specific language.\n\nFamiliarity with machine learning concepts, neural networks, or frameworks such as PyTorch or TensorFlow.\n\nExposure to numerical computing, linear algebra, or HPC kernels.\n\nExperience using profiling, benchmarking, or performance analysis tools.\n\nFamiliarity with library or API development practices.\n\nWhy Join Cerebras\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\nBuild a breakthrough AI platform beyond the constraints of the GPU.\n\nPublish and open source their cutting-edge AI research.\n\nWork on one of the fastest AI supercomputers in the world.\n\nEnjoy job stability with startup vitality.\n\nOur simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here!\nApply today and become part of the forefront of groundbreaking advancements in AI!\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\nThis website or its third-party tools process personal data. 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