AI Research Engineer – Deep Learning (Remote/Hybrid, Zurich)

About the role

We are seeking an AI Research Engineer to design and develop next‑generation deep‑learning models and training systems. The role sits at the intersection of research and production, allowing you to experiment with cutting‑edge techniques while delivering scalable solutions for real‑world applications.

Key responsibilities

• Design, implement and evaluate advanced deep‑learning architectures, including large‑scale transformer models.
• Build and optimise distributed training pipelines for GPU‑based workloads.
• Improve model efficiency, performance and inference capabilities.
• Collaborate with AI scientists, infrastructure and product engineering teams to ensure production‑ready AI systems.
• Conduct experimentation, benchmarking and technical research on representation learning, multimodal systems and model scalability.

Required profile

• 4+ years of professional experience in AI, machine learning or deep‑learning engineering.
• Strong proficiency in Python and hands‑on experience with PyTorch.
• Demonstrated work with transformer architectures and large‑scale model training.
• Experience in distributed training environments and GPU optimisation.
• Solid understanding of model optimisation, training workflows and handling large datasets.

Required skills

• Python
• PyTorch
• Transformer architectures
• Distributed training
• GPU programming / CUDA
• High‑performance ML infrastructure
• Large‑scale training pipelines
• Model optimisation techniques

What we offer

• Remote‑first flexibility with a hybrid office in Zurich.
• Opportunity to work on cutting‑edge AI research and large‑scale model development.
• Collaboration with highly technical AI and engineering teams.