FriendliAI
Software Engineer AI Inference Engine Engineer
FriendliAI, San Francisco, California, United States, 94199
Overview
FriendliAI, a Redwood City, CA-based startup, is building the next-generation AI inference platform that accelerates the deployment of large language and multimodal models with unmatched performance and efficiency. Our infrastructure supports high-throughput, low-latency AI workloads for organizations worldwide. We are also integrated with the Hugging Face platform, allowing instant access to over 400,000 open-source models. We are on a mission to deliver the worlds best platform for generative and agentic AI. The Role We are seeking a highly technical Inference Engine Engineer to optimize the performance and efficiency of our core inference engine. You will focus on designing, implementing, and optimizing GPU kernels and supporting infrastructure for next-generation generative and agentic AI workloads. Your work will directly power the most latency-critical and compute-intensive systems deployed by our customers. The Person You are an exceptional engineer with a strong foundation in GPU programming and compiler infrastructure. You enjoy pushing the performance boundaries and have experience supporting production-scale machine learning applications. Key Responsibilities Design and optimize custom GPU kernels for AI (e.g., transformer and diffusion) workloads Contribute to the development of FriendliAIs kernel compiler, memory planner, runtime, and other core components Collaborate with cloud and infrastructure engineers to ensure end-to-end inference performance Analyze performance bottlenecks across the software and hardware stack, and implement targeted optimizations Drive support for new model architectures and tensor compute patterns Maintain production-grade performance infrastructure, including profiling, benchmarking, and validation tools Qualifications 5+ years of experience in production or high-impact research environments Production-level expertise in Python and C++ Bachelors or Masters degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent Experience developing machine learning frameworks or performance-critical runtime systems Hands-on experience writing and optimizing GPU kernels Hands-on experience profiling GPU kernels Experience working with generative AI models such as transformer and diffusion models Preferred Experience Experience developing machine learning compilers or code generation systems Familiarity with dynamic shape compilation, memory planning, and kernel fusion Contributions to inference engines, compilers, or high-performance numerical libraries Understanding of multi-GPU and distributed inference strategies Unlimited snacks and beverages Supportive work environment Employment details Seniority level: Mid-Senior level Employment type: Full-time Job function: Engineering and Information Technology Industries: Software Development Were unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI. #J-18808-Ljbffr
FriendliAI, a Redwood City, CA-based startup, is building the next-generation AI inference platform that accelerates the deployment of large language and multimodal models with unmatched performance and efficiency. Our infrastructure supports high-throughput, low-latency AI workloads for organizations worldwide. We are also integrated with the Hugging Face platform, allowing instant access to over 400,000 open-source models. We are on a mission to deliver the worlds best platform for generative and agentic AI. The Role We are seeking a highly technical Inference Engine Engineer to optimize the performance and efficiency of our core inference engine. You will focus on designing, implementing, and optimizing GPU kernels and supporting infrastructure for next-generation generative and agentic AI workloads. Your work will directly power the most latency-critical and compute-intensive systems deployed by our customers. The Person You are an exceptional engineer with a strong foundation in GPU programming and compiler infrastructure. You enjoy pushing the performance boundaries and have experience supporting production-scale machine learning applications. Key Responsibilities Design and optimize custom GPU kernels for AI (e.g., transformer and diffusion) workloads Contribute to the development of FriendliAIs kernel compiler, memory planner, runtime, and other core components Collaborate with cloud and infrastructure engineers to ensure end-to-end inference performance Analyze performance bottlenecks across the software and hardware stack, and implement targeted optimizations Drive support for new model architectures and tensor compute patterns Maintain production-grade performance infrastructure, including profiling, benchmarking, and validation tools Qualifications 5+ years of experience in production or high-impact research environments Production-level expertise in Python and C++ Bachelors or Masters degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent Experience developing machine learning frameworks or performance-critical runtime systems Hands-on experience writing and optimizing GPU kernels Hands-on experience profiling GPU kernels Experience working with generative AI models such as transformer and diffusion models Preferred Experience Experience developing machine learning compilers or code generation systems Familiarity with dynamic shape compilation, memory planning, and kernel fusion Contributions to inference engines, compilers, or high-performance numerical libraries Understanding of multi-GPU and distributed inference strategies Unlimited snacks and beverages Supportive work environment Employment details Seniority level: Mid-Senior level Employment type: Full-time Job function: Engineering and Information Technology Industries: Software Development Were unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI. #J-18808-Ljbffr