Technical Leader – AI Systems Architecture

Overview

Technical Leader – AI Systems Architecture

Computer Architecture Innovation Lab

📍 Zurich, Switzerland | Fully Onsite

• We are seeking a senior technical leader and researcher to join our newly established Computer Architecture Innovation Lab. This role focuses on multimodal AI systems, large-scale model training and inference, and close collaboration with architecture, systems, and research teams.
• A strong open-source track record is essential. Candidates should be active contributors or maintainers in major AI frameworks or communities.
• Design and implement end-to-end pipelines, covering: data preprocessing, distributed training, evaluation and benchmarking.
• Focus on memory efficiency, parallelism strategies, and system-level bottleneck analysis to optimize AI performance.
• Collaborate with Systems, Hardware Architecture and Applied Research teams to bridge research and production systems.
• Contribute to open-source community development; maintainer or committer experience is a strong plus.
• Aim to lead open-source leadership and real community impact within the role and the Lab.

• Core Expertise — Deep expertise in multimodal learning, with hands-on experience training large multimodal models (LMMs).
• Experience with efficient inference and deployment of large models.
• Proven open-source contributions, ideally to projects such as:
  • Hugging Face Transformers
  • LLaVA, BLIP-2, InternVL
  • OpenMMLab, Diffusers
• Technical Skills — expert-level proficiency in PyTorch and or JAX; experience with large-scale distributed training and inference.
• Strong understanding of AI performance optimization, including memory efficiency, parallelism strategies, and system-level bottleneck analysis.
• Ability to design and implement end-to-end pipelines, covering data preprocessing, distributed training, and evaluation/benchmarking.
• Hands-on experience in open-source community development (maintainer/committer experience is a strong plus).
• Research and Innovation — Strong publication record in top-tier AI conferences (e.g., ACL, EMNLP) and demonstrated ability to propose novel architectures or algorithms, validate ideas through rigorous experimentation, and bridge research and production systems.
• Background and Profile — PhD plus 8+ years of experience in
  • Computer Science
  • AI or related fields
• Excellent English communication and documentation skills and ability to work in cross-functional and interdisciplinary teams including Systems, Hardware Architecture, and Applied Research.
• Location and Work Style — Fully onsite role; open-source leadership and real community impact are key selection criteria.