Machine Learning Engineer

ML Infrastructure Engineer - Zurich (Hybrid) - CHF 180-300 Benefits

I am supporting well funded startup who are looking for an ML Infrastructure Engineer to build the platforms, tooling, and distributed systems that enable AI-driven semiconductor design. You'll work alongside ML researchers, EDA engineers, and chip designers to scale training, deployment, and data infrastructure for next-generation silicon development.

Responsibilities

• Build and maintain ML infrastructure for training and deploying models at scale.
• Develop distributed training environments using PyTorch, Kubernetes, Ray, and GPU clusters.
• Create data pipelines for large engineering and semiconductor datasets.
• Improve MLOps workflows, CI/CD, monitoring, and experiment reproducibility.
• Optimise performance across cloud and on-prem HPC environments.
• Partner with ML and chip design teams to productionise AI solutions.

Requirements

• 3 years' experience in ML Engineering, MLOps, Platform Engineering, or Infrastructure Engineering.
• Strong Python and Linux skills
• PyTorch
• Kubernetes & Docker
• AWS, Azure, or GCP
• CI/CD pipelines
• Distributed training frameworks (Ray, DeepSpeed, PyTorch Distributed)
• Experience managing GPU-based training workloads

Nice to Have

• Semiconductor, ASIC, FPGA, SoC, or EDA experience
• Familiarity with Synopsys, Cadence, Siemens EDA, or HPC environments
• Exposure to LLMs, reinforcement learning, or graph neural networks

Apply or drop me a message for a confidential chat!

Leroy.Clarke@IC-Resources.com