{"id":701884,"url":"https://alion.io/job/inferact-member-of-technical-staff-kernel-engineering","title":"Member of Technical Staff, Kernel Engineering","company":{"id":678585,"name":"Inferact","domain":"inferact.ai","url":"https://alion.io/company/inferact","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":87,"open_postings":27,"ghost_share":0,"stale_share":0.519,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-20T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":200000,"max":400000,"currency":"USD","period":"year","gross":null,"usd_annual":400000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"CUDA","optional":false},{"name":"CUDA Toolkit","optional":false},{"name":"Python","optional":false},{"name":"Triton","optional":false},{"name":"vLLM","optional":false},{"name":"LLVM","optional":true},{"name":"MLIR","optional":true},{"name":"Quantization","optional":true},{"name":"TPU","optional":true},{"name":"XLA","optional":true}],"status":"live","first_seen_at":"2026-06-24T05:29:46Z","employer_posted_date":"2026-06-24","last_verified_at":"2026-10-20T20:52:47Z","board_verified":true,"closed_at":null,"days_open":118,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":117},"description":"Inferact's mission is to grow vLLM as the world's AI inference engine and accelerate AI progress by making inference cheaper and faster. Founded by the creators and core maintainers of vLLM, we sit at the intersection of models and hardware-a position that took years to build.\nAbout the Role\nWe're looking for a performance engineer to squeeze every FLOP out of modern accelerators. You'll write the kernels and low-level optimizations that make vLLM the fastest inference engine in the world. Your code will run on hundreds of accelerator types, from NVIDIA GPUs to emerging silicon. When hardware vendors develop new chips, they integrate with vLLM. You'll work directly with these teams to ensure we're extracting maximum performance from every generation of hardware.\nSkills and Qualifications\nMinimum qualifications:\nBachelor's degree or equivalent experience in computer science, engineering, or similar.\n\nDeep experience writing CUDA kernels or equivalent (CuTeDSL, Triton, TileLang, Pallas).\n\nStrong understanding of GPU architecture: memory hierarchy, warp scheduling, tiling, tensor cores.\n\nProficiency in C++ and Python with demonstrated ability to write high-performance code.\n\nExperience with profiling tools (Nsight, rocprof) and performance optimization methodologies.\n\nObsession with benchmarks and squeezing every percentage point of speedup.\n\nPreferred qualifications:\nExperience with ML-specific kernel optimization (FlashAttention, fused kernels).\n\nKnowledge of quantization techniques (INT8, FP8, mixed-precision).\n\nFamiliarity with multiple accelerator platforms (NVIDIA, AMD, TPU, Intel).\n\nExperience with compiler technologies (LLVM, MLIR, XLA).\n\nBonus points if you have:\nKernel-related contributions to vLLM or other inference engine projects.\n\nContributions to open-source GPU, ML systems, or compiler optimization projects\n\nWritten deep technical blogs on GPU optimization.\n\nLogistics\nLocation: This role is based in Singapore.\n\nCompensation: Depending on background, skills, and experience, the expected annual salary range for this position is S$200,000 to S$400,000 annually + equity.\n\nVisa sponsorship: We sponsor visas on a case-by-case basis.\n\nBenefits: Inferact offers a generous benefits package, including medical, dental, and vision 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