Data Center AI SoC & System Architect

Teknik, data och digitalt · Mjukvaru- och webbutveckling · Mjukvaruutveckling

I korthet

Qualcomm seeks an experienced Data Center AI SoC & System Architect in Grenoble, France, to design next-generation cloud AI systems and accelerators for generative AI inference. The role involves defining SoC and system specifications, conducting architecture studies, and collaborating across teams to deliver market-leading solutions.

Ansvarsområden

Partner across architecture, design, systems, product, software, platform, and customer teams to deliver market-leading data center systems.
Translate product and workload requirements into SoC and system specifications.
Drive feature-set requirements into technology, IP, platform, and software teams.
Execute SoC and system architecture studies, product definition, and implementation guidance.
Quantify performance, power, area, cost, capacity, memory bandwidth, network topology/bandwidth/latency, and scalability tradeoffs.
Drive analysis methods and tools.
Follow designs through implementation and production.
Correlate observed system performance with models and targets, identify root causes of gaps, and drive performance to closure.
Execute competitive analysis across SoC, platform, system, compute, memory, data center networking, software, and deployment considerations.
Support and mentor technical contributors and generate innovations and patents.

Krav

MS or PhD in EE, ECE, CE, CS, or a related field.
7+ years of relevant experience in SoC, platform, or system architecture; AI accelerators; memory architecture; or memory technologies.
Ability to collaborate across teams, build alignment, and contribute to technical direction.
Computer and system architecture expertise spanning one or more of processors, accelerators, memory systems, data center network fabrics, interconnects, hardware/software interfaces, platform topology, and SoC and system implementation tradeoffs.
Ability to execute quantitative SoC, system, and competitive studies using high-level calculators, spreadsheets, analytical models, profilers, and functional or performance simulators.
Experience developing architecture methodologies, tools, and analysis frameworks and translating findings into actionable recommendations.
Experience correlating modeled and measured system performance, isolating hardware and software bottlenecks, and driving cross-functional performance closure through production.
Excellent technical communication, documentation, and interpersonal skills, including presenting to technical and business stakeholders.
Self-directed execution, mentorship of others, and rigorous attention to accuracy.
Understanding of generative AI and machine-learning workloads, especially Large Language Model inference and accelerator bottlenecks.
Experience in processor, accelerator, or system architecture, including ISA design, microarchitecture, performance modeling, system topology, scale-up or scale-out networks, or hardware/software co-design.
Knowledge of DRAM and memory-controller architecture, bandwidth, latency, and power tradeoffs, protocols such as LPDDR, HBM, DDR, or GDDR, and emerging technologies such as processing-in-memory, processing-near-memory, or 3D integration.
Expertise in one or more data center SoC or system technologies such as RAS, ECC, security, encryption, Ethernet or InfiniBand networking, RDMA, network interface controllers, switches, congestion control, chip-to-chip or die-to-die protocols, chiplets, PHYs, power and thermals, advanced packaging, platform management, or system scalability.
Programming ability for architecture modeling and automation; object-oriented C++ and Python preferred.
Fluent with using AI to accelerate workflows.
Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience.
Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience.
PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.
2+ years of work experience with Programming Language such as C, C++, Java, Python, etc.