Hp Principal AI Runtime & Performance Lead to define architecture and performance strategy for AI workloads across HP PCs. Lead technical direction and guide implementation teams on model execution and resource allocation.
Responsibilities
We are looking for a Principal AI Runtime & Performance Lead to define the architecture and performance strategy for AI workloads across HP PCs. You will establish how software should use compute engines, memory, hardware capabilities, and different model types to deliver responsive, efficient, and reliable AI experiences. As a senior technical leader, you will translate product goals into system-level performance requirements and architectural direction. You will guide decisions about model execution, resource allocation, and runtime behavior across CPUs, GPUs, and NPUs, considering the constraints of different device configurations. The role emphasizes architectural planning and technical leadership. You will set the direction for implementation and optimization teams, establish how performance should be measured, and use evidence from prototypes, benchmarks, and telemetry to refine the architecture.
What You Might Do
Own the technical direction for AI runtime architecture and performance across supported PC platforms and hardware configurations.
Define model execution strategies across CPU, GPU, and NPU resources, balancing responsiveness, throughput, memory use, power consumption, and thermal constraints.
Determine how different model types and workload patterns should influence runtime design, hardware utilization, and resource allocation.
Establish architectural approaches for concurrent agents and models, including resource coordination and behavior under system pressure.
Translate customer experience goals into performance budgets, system requirements, and design principles that engineering teams can implement.
Define benchmark methodology and representative workload scenarios to evaluate architectural choices and measure progress against performance goals.
Guide cross-functional teams through design reviews, resolve technical trade-offs, and prioritize improvements based on system-level impact.
Partner with hardware, firmware, operating system, platform, and AI engineering teams to align capabilities and dependencies across the stack.
Shape engineering roadmaps, evaluate emerging technologies through proofs of concept, and mentor engineers on runtime architecture and performance design.
Essential Qualifications
Qualification
Experience with edge AI platformsKnowledge of model architecturesFamiliarity with firmware integrationThe pay range for this role is $147
Preferred
Experience with edge AI platforms, on-device inference, and performance planning for commercial PCs.
Familiarity with inference frameworks such as ONNX Runtime, TensorRT, and OpenVINO and their hardware execution backends.
Knowledge of model architectures, quantization, and the relationship between model characteristics, memory footprint, and execution performance.
Experience using device telemetry to understand workload behavior and inform architectural decisions.
Familiarity with firmware integration, hardware resource controls, and power and thermal management.
Strong C++ and Python background to support technical reviews, architectural prototyping, and collaboration with implementation teams.
The pay range for this role is $147,050 to $230,850 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience.
