Lead LLM inference optimization for Qualcomm Cloud AI accelerators, working with customers and internal teams to deploy and tune generative AI workloads.
Responsibilities
Deploy and optimize LLM and multimodal inference workloads on Qualcomm Cloud AI accelerator platforms
Profile and optimize prefill and decode performance metrics
Analyze model architecture and runtime bottlenecks across compute, accelerator memory, host memory, KV cache, interconnect, networking, and software stack
Optimize model execution using quantization, batching, continuous/dynamic batching, KV-cache management, paged attention, prompt/context-length tuning, and speculative decoding
Optimize distributed inference across tensor, pipeline, data, context, and expert parallelism
Requirements
Master’s degree or higher in Computer Science, Electrical/Computer Engineering, AI/ML, or related technical field
Participate in complex technical issues and initiatives related to large scale applications, systems, databases, or other technical products and services, providing L2 production support for cloud-hosted applications and platforms.
Responsibilities
Participate in complex technical issues and initiatives related to large scale applications, systems, databases, or other technical products and services
Identify opportunity for process improvements within technical support strategies and plans
Review and analyze technical queries to extract data, create standard databases, or perform limited programming to fine tune systems supporting low to medium risk technical deliverables
Present recommendations for resolving complex technical queries
Exercise some independent judgment to analyze performance trends and recommend process improvements while developing understanding of technical process controls or standards
Requirements
Bachelor’s degree in Computer Science
Information Technology
Engineering
related technical field
Nice to have: Red Hat Certified System Administrator/Engineer
Lead the modernization of the company's Cloud Engineering, Platform Engineering, Infrastructure Engineering, Network Engineering, Site Reliability Engineering, and Enterprise Infrastructure Operations.
Responsibilities
Define and execute the multi-year cloud migration roadmap
Lead migration of application workloads from on-premises infrastructure to AWS
Build the foundation other engineers stand on, including service frameworks, shared libraries, observability, and resilience for Nominal’s mission-critical software.
Responsibilities
Build service frameworks and shared libraries for Nominal services
Build the data foundation every application stands on, owning the compute layer between Nominal's engine and the user, and ensuring high-performance, correct, and observable data handling.
Responsibilities
Own the layer between Nominal's compute engine and the user: streaming over WebSockets, orchestrating web workers, handling columnar data formats, caching intelligently, and processing live and historical data on the client.
Design generalized data and compute capabilities that serve today's product and the use cases we haven't met yet.
Validate workflows directly with users and make confident product decisions when requirements are incomplete.
Expose new features from the compute layer in a composable, scalable form for end users.
Design experiences that expose powerful capabilities without overwhelming users.
Lead the Ubuntu Foundations Package Management team, combining people management with active engineering involvement to define technical direction, grow engineering talent, and ensure the continued evolution of Ubuntu's package management and system lifecycle technologies.
Responsibilities
Define technical vision and roadmap for Ubuntu's package management and system lifecycle platform
Participate in design reviews and key technical decisions affecting software management and system lifecycle technologies
Promote high standards for performance, reliability, security, and maintainability
Lead and support a team of engineers responsible for key Ubuntu platform technologies
Mentor and grow engineers, helping them expand their technical leadership, ownership, and organizational impact
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