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Field
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with thousands of CPUs and GPUs, petabytes of storage, and high-speed, low-latency networks across multiple data centres in Switzerland. As research workloads continue to evolve, we are building a hybrid
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, or Transformer-based architectures Familiarity with training and evaluating models on GPU-accelerated hardware Ability to build reproducible experiments and maintain clear documentation Integrating AI/ML models
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evaluating them with clear performance criteria. Familiarity with real-time systems, embedded computing or GPU optimisation. Strong problem-solving and analytical skills. Fluent English, both written and
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Linux/Unix, and running algorithms on CPUs and GPUs Deep learning frameworks, particularly Python and PyTorch Medical image segmentation and computer vision model development Large language models and
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-day reliability and long-term evolution of clustered compute, GPU resources, high-performance storage, and the scheduler/tooling that support research at scale. Drives a culture of operational
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analytics techniques Familiarity with C++ and GPU programming Familiarity with Python programming Experience with modern software development practices to ensure code quality Experience with computational
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infrastructure, including Docker-based microservices, large language model (LLM) inference servers on GPU clusters, vector database and retrieval-augmented generation (RAG) pipelines, and observability stacks
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with GPU-based code development (e.g., CUDA). - Familiarity with AI/ML development concepts such as RL, RAG, MCP, Agentic AI, multi-modal learning, etc. - Familiarity with AI/ML development tools such as
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of bioacoustic signals. Extensive experience with programming (Matlab, R, Python) including GPU programming is required, and familiarity with edge-based machine learning (particularly sound event detection), open
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routine maintenance on fixed and rotary wing aircraft. Operate and maintain ground support equipment (e.g., tugs, forklifts, GPUs, snow plows, vehicles). Maintain and set up hangar, lab, and shop areas