Description
We are seeking a senior software engineer to automate and optimise performance analysis workflows for AI training and inference workloads. You will not only perform analysis but also reshape how it's done, building tools and workflows that scale across a broad audience of engineers.
The successful candidate will design and build performance analysis tools and workflows for AI training and inference workloads. They will understand how AI performance engineers work and translate their needs into scalable, intuitive tooling. The candidate will develop integrations between profiling infrastructure and AI frameworks and workflows, collaborate with performance engineers, hardware architects, and software teams to ensure profiling capabilities align with real-world AI workloads, identify performance bottlenecks in AI workloads and develop automated approaches to detect and diagnose them.
To be successful in this role, you will require a M.S., or PhD in Computer Science, Computer Engineering, or a related field (or equivalent experience) with 6+ years of relevant work experience. You will need deep knowledge of AI workloads, frameworks, and performance characteristics, experience building tools, workflows, or infrastructure used by other engineers, strong software development skills (Python, C++ preferred), ability to translate user requirements into scalable tooling solutions, up-to-date with AI-enabled tooling for software development and performance analysis, and strong interpersonal skills for understanding engineer difficulties and working across multi-functional teams.
Experience profiling or optimising AI training or inference pipelines at scale, background building developer tools or platforms for ML engineers, contributions to open-source AI tooling or frameworks will be considered as ways to stand out from the crowd.