{"id":678935,"url":"https://alion.io/job/friendli-software-engineer-gpu-kernel-2","title":"Software Engineer – GPU Kernel","company":{"id":673295,"name":"FriendliAI","domain":"friendli.ai","url":"https://alion.io/company/friendli","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"C","score":68,"open_postings":17,"ghost_share":0.529,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-04T06:34:25Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":156000,"max_usd":302000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":508},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"CUDA","optional":false},{"name":"HPC","optional":false},{"name":"Hugging Face","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Quantization","optional":false},{"name":"ROCm","optional":false},{"name":"CUTLASS","optional":true},{"name":"Mixture of Experts","optional":true},{"name":"Triton","optional":true}],"status":"live","first_seen_at":"2026-03-15T13:19:53Z","employer_posted_date":"2026-03-15","last_verified_at":"2026-11-04T09:12:39Z","board_verified":true,"closed_at":null,"days_open":233,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":233},"description":"About the job\nFriendliAI is looking for a GPU Kernel Engineer to design, build, and optimize the low-level compute kernels that power our large-scale, GPU-accelerated AI inference platform. You will be delivering world-class inference speed across NVIDIA and AMD GPUs. With our recent $20M funding, we are scaling our team to meet market demand.\nThis is a deeply technical, high-impact role where you will write GPU code, implement advanced optimizations. As part of our engine team, you will contribute directly to the company’s proprietary inference engine which supports over 600,000 models on Hugging Face. You will work with the inventors of continuous batching and collaborate with the platform team to deploy your work into production.\nKey Responsibilities\nDesign, implement, and optimize high-performance GPU kernels for AI inference (e.g., GEMM, attention, routing)\n\nDevelop and maintain GPU code in CUDA and C++, including low-level assembly when needed\n\nImplement reduced-precision and quantized kernels (FP8/FP4) for low-latency or high-throughput inference\n\nBenchmark and ensure cross-vendor performance parity between NVIDIA and AMD hardware\n\nContribute to internal GPU libraries and tune performance of performance-critical components\n\nAccelerate multi-modal model pipelines\n\nInvestigate and integrate next-generation GPU features\n\nQualifications\n3+ years of experience in GPU programming, HPC, or performance-critical systems\n\nBachelor’s or Master’s degrees in Computer Science, Computer Engineering, Electrical Engineering, or a related field\n\nStrong proficiency in CUDA for NVIDIA GPUs or ROCm/HIP for AMD GPUs\n\nDeep understanding of GPU architecture: warps, threads, memory hierarchy, synchronization, and latency-throughput trade-offs\n\nProficiency in C++\n\nExperience with GPU profiling and performance tuning\n\nStrong numerical background with understanding of precision trade-offs and quantization techniques\n\nPreferred Experience\nExperience optimizing transformer, multi-modal, or Mixture-of-Experts (MoE) architectures at the kernel level\n\nFamiliarity with the latest GPU libraries and frameworks (CUTLASS, Triton, …)\n\nInter-GPU communication programming experience\n\nOpen-source contributions related to GPU performance or ML acceleration\n\nResearch or conference presentations on GPU optimization, HPC, or numerical computing\n\nBenefits\nFlexible working hours\n\nDaily lunch and dinner provided; unlimited snacks and beverages\n\nSupportive and highly collaborative work environment\n\nHealth check-up support and top-tier equipment/hardware support\n\nA front-row seat to the generative AI infrastructure revolution\n\nCompetitive compensation, startup equity, health insurance, and other benefits.\n\nAbout FriendliAI\nFriendliAI is building the world’s best AI inference platform that makes large language and multi-modal models fast, efficient, and deployable at scale. We power high-throughput, low-latency AI workloads for organizations worldwide and integrate directly with Hugging Face, giving developers instant access to over 600,000 open-source models.\nWe are a small, fast-moving team doing work that matters at one of the most exciting moments in the history of technology. 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