Kernelize
Artificial Intelligence • Hardware • SaaS
Kernelize is a company that builds a Triton-based platform and backend plugins to enable day-0 LLM model support across CPUs, GPUs, and NPUs. They provide Triton and vLLM backend integrations, optimized kernels, and compiler expertise to accelerate and simplify LLM inference on diverse hardware, helping teams integrate high-performance kernels into existing ML stacks and reduce development delays. Kernelize leverages the Triton open-source compiler community and focuses on hardware-agnostic, performance-oriented AI inference tooling for organizations deploying large language models.
Compiler Engineer – Kernelize
Job not on LinkedIn
October 22
Kernelize
Artificial Intelligence • Hardware • SaaS
Kernelize is a company that builds a Triton-based platform and backend plugins to enable day-0 LLM model support across CPUs, GPUs, and NPUs. They provide Triton and vLLM backend integrations, optimized kernels, and compiler expertise to accelerate and simplify LLM inference on diverse hardware, helping teams integrate high-performance kernels into existing ML stacks and reduce development delays. Kernelize leverages the Triton open-source compiler community and focuses on hardware-agnostic, performance-oriented AI inference tooling for organizations deploying large language models.
📋 Description
• Work on cutting-edge compiler technologies and help shape the core of our tech from the ground up.
🎯 Requirements
• Passionate about low-level optimizations, code generation, and pushing performance to the next level. • Experience in building custom backends for IP accelerators on Triton.
🏖️ Benefits
• The actual offer, reflecting the total compensation package and benefits, will be at the company’s sole discretion and determined by a myriad of factors, including, but not limited to, years of experience, depth of skills, and other relevant business considerations. • The company also reserves the right to amend or modify employee perks and benefits. • At Kernelize we consider several factors when setting each role’s salary range, including the competitive benchmarking data for the market and geographic location.
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