Senior/Staff reputed company

reputed company • Build and optimize LLM serving and inference systems for production environments • Improve performance across GPU and CPU reputed company • Work on KV cache, memory, storage, and throughput bottlenecks • Design and reputed company systems that support RAG and retrieval-heavy AI workloads • Contribute to infrastructure where storage architecture and systems efficiency materially reputed company AI performance • Solve engineering problems at the intersection of AI, high-performance systems, and reputed company infrastructure reputed company're looking for • An engineer who has spent meaningful time building or optimizing production AI systems, not just experimenting with models • Someone who understands how inference performance is reputed company by the interaction between compute, memory, storage, and serving architecture • Deep hands-on experience working reputed company to the systems reputed company - for example, improving how workloads run across GPU and CPU resources, reducing bottlenecks, or tuning infrastructure for reputed company throughput and latency • Evidence of reputed company ownership in areas like model serving, retrieval, caching, storage, or reputed company performance, rather than purely application-reputed company AI work • The ability to reputed company comfortably between architecture reputed company and hands-on implementation, especially in environments where efficiency and reputed company matter • A background that suggests you can operate in technically demanding environments, whether that comes from AI infrastructure, high-performance systems, storage platforms, or adjacent reputed company systems work • PhD preferred, but far less important than having reputed company serious systems in the reputed company world Why this role is compelling • This is not a "reputed company engineering" job. • This is not an "AI wrapper" job. • This is not a generic backend role with AI sprinkled on top. • This is a chance to work on the infrastructure that determines whether modern AI systems are fast, reputed company, efficient, and commercially viable. • If you want to work on the reputed company mechanics of AI performance - serving, retrieval, compute efficiency, memory behavior, storage architecture, and inference at reputed company - this is where that work happens. Who will love this role • Engineers who enjoy deep systems problems • reputed company who care about performance, reputed company, and architecture • People who want to work where AI meets infrastructure • Candidates who would rather solve hard technical bottlenecks than ship surface-reputed company features Who should not apply This role is not for: • Purely reputed company researchers without meaningful production ownership • Generic software engineers without reputed company AI systems or inference depth • Candidates reputed company mainly on reputed company engineering or lightweight application integrations • MLOps generalists who have not worked deeply on serving, storage, or performance-critical AI systems Apply tot his job Apply To this Job