Description
AI Infrastructure Engineer (Compute/GPU)
Location: Zürich
Department: AI & Software
Location Type: IN_OFFICE
Employment Type: FULL_TIME
mimic is an early-stage deep tech robotics & AI start-up based in Zurich and supported by leading VCs. We give industry workers a helping hand for tedious manual labour tasks and mitigate labour shortages with a versatile automation platform. Our automation solutions, driven by dexterous robotic hands and cutting-edge AI trained on human observations, bring a new level of AI embodiment to the real world.
The Role
We are looking for an AI Infrastructure Engineer (Compute/GPU) to own and optimize the compute backbone of our AI systems.
Your mission is simple but high-impact: make our models train and run faster, more efficiently, and at lower cost, without sacrificing performance. You will be responsible for identifying bottlenecks across training and inference, designing scalable multi-node GPU systems, and ensuring we get maximum leverage from our compute resources.
You will work at the intersection of deep learning, distributed systems, and cloud infrastructure, enabling the AI team to push model performance while maintaining speed and cost efficiency.
What you’ll do
- Identify and eliminate bottlenecks in training and inference (GPU utilization, memory constraints, data loading, communication overhead).
- Optimize distributed training setups (multi-node, multi-GPU, model/data parallelism, sharding strategies).
- Own architecture decisions for large-scale model training.
- Support productionization of our AI models.
- Benchmark and integrate different cloud providers for cost and performance.
- Collaborate closely with researchers and engineers to accelerate experimentation cycles.
Who you are
- 3+ years of experience in ML systems, distributed training, or AI infrastructure.
- Hands-on experience with large-scale deep learning training (e.g., PyTorch Distributed, FSDP, Megatron, K8, etc.).
- Deep understanding of GPU architectures, memory systems, debugging and optimizing CUDA/NCCL or similar.
- Proven ability to optimize model training speed, stability, and cost.
- Experience with some major cloud provider (AWS, GCP, or smaller providers like Lambda Labs, Runpod) and managing GPU clusters.
- Strong systems thinking and ownership mindset.
- Clear communicator and fluent English speaker.
Nice to have
- Experience in robotics.
- Familiarity with imitation learning, vision-language-action models, or large-scale transformer training.
- Background in high-performance computing (HPC).
You will have the opportunity to shape a robotics & AI company from the ground up. In flat hierarchies, you will work directly with the founders and some of the best talents in the robotics space. At mimic, you are accepted for who you are. As part of our ongoing journey to create a diverse and inclusive environment, we encourage everyone to apply.
We look forward to you bringing your knowledge, personal experiences, and fresh perspectives. Together, we can solve some of the greatest challenges in robotics.
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