At Red Hat we believe the future of AI is open and we are on a mission to bring the power of open-source LLMs to every enterprise. We are looking for a Software Engineer. The task involves integrating LLM inference performance benchmarking tools like LLM load test, guide llm, and lm-eval into Crucible, our comprehensive benchmarking framework. The process includes documenting the installation and basic test execution procedures, automating these procedures using scripts, setting up the test scenario, and automating the execution procedure. The goal is to ensure the workload setup is clearly documented, the installation and basic test execution are automated, and the directory is referenced in the relevant story. This integration aims to enhance our benchmarking capabilities, enabling more accurate and efficient evaluation of different language models. Primary Job Responsibilities: Develop and maintain tools and automation software to aid the performance and benchmarking work for the team like Crucible, GuideLLM and other software tools Formulate test plans, and execute performance and evaluation benchmarks against various instructlab workloads and models to characterize performance, drive performance improvements, and detect performance regressions through data analysis and visualization Collaborate with other engineering teams to resolve performance issues Triage, debug, and solve customer cases related to instructlab performance Submit performance benchmarking results to industry consortia Publish results, conclusions, recommendations and best practices via internal test reports, presentations, external blogs and official documentation to support our partners and customers. Participate in internal and external conferences about your work and results Required Skills: Programming experience in Python and other various system scripting languages Familiar with various public clouds and how to provision new systems Knowledge of popular databases including NoSQL databases like ElasticSearch and SQL databases like postgres Performance benchmarking, data capture, data analysis, and data Experience with performance data collection and analysis tools Knowledge of popular AI technologies, and frameworks Knowledge of large language model inference and finetuning internals Experience working with the Linux operating system Excellent written and verbal language skills in English Nice to Haves: Masters degree or Phd in Computer Science or related fields Knowledge of AI performance benchmarking suites such as MLPerf Direct experience working with AI performance profiling tools like GuideLLM Experience in the k8s ecosystem, preferably the OpenShift ecosystem Familiarity with the modern "accelerator" ecosystem, models, drivers, interconnects
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