Member of Technical Staff, Software Co-Design AI HPC Systems (AI)

TL;DR

Member of Technical Staff, Software Co-Design AI HPC Systems (AI): Architecting and productionizing next-generation AI systems at datacenter scale with an accent on hardware-software co-design, optimizing performance, efficiency, and scalability across models, systems software, networking, storage, and AI hardware. Focus on analyzing production workloads, developing performance models, co-designing parallelism strategies, and influencing hardware roadmaps for large-scale training and inference.

Location: Zürich, Switzerland. Expected to work from designated hirify.global office at least four days a week if living within 25 miles

Company

hirify.global AI’s Superintelligence Team (MAIST) – a startup-like team pushing boundaries toward controllable, safety-aligned AI systems that amplify human potential.

What you will do

• Lead co-design of AI systems across hardware and software, including accelerators, interconnects, memory, storage, runtimes, and distributed frameworks.
• Analyze workloads to identify bottlenecks and drive architectural decisions for compute, communication, and data movement.
• Optimize parallelism, execution models, and distributed algorithms for scalability, utilization, reliability, and cost efficiency.
• Develop performance models to project system behavior and guide hardware roadmaps.
• Partner with compiler, kernel, and runtime teams to maximize accelerator performance via custom kernels and optimizations.
• Influence AI hardware design at system and silicon levels, prototype ideas, and mentor engineers.

Requirements

• Bachelor’s in Computer Science, Computer Engineering, Electrical Engineering or equivalent
• 10+ years in systems software, hardware architecture, or AI infrastructure with scale impact
• Strong background in AI accelerators/GPUs, distributed AI training/inference, HPC, ML systems, performance modeling, or hardware-software co-design
• Proficiency in C/C++, CUDA, Python, and performance-critical software
• Ability to influence across teams and stakeholders

Nice to have

• Experience with large-scale AI clusters
• Familiarity with LLMs, multimodal models, or recommendation systems
• Knowledge of interconnects like NCCL, MPI, RDMA
• Performance modeling for future hardware
• Contributions to hardware roadmaps or publications in systems/ML

Culture & Benefits

• Growth mindset, innovation, collaboration with values of respect, integrity, accountability
• Inclusion culture where everyone thrives
• End-to-end ownership, technical rigor, bias toward real-world impact
• Contributions to research community via publications and open-source
• Partnerships with product teams reaching billions of users