Senior AI Infrastructure Engineer (Zürich, 100%)

As an AI infrastructure SWE you will build the systems that underpin our robot learning. You will work across data pipelines, internal tooling, and model deployment from day one as we build the foundations of our ML infrastructure.

What you'll be doing:

• Build a tiered data processing platform from raw ingestion to versioned training dataset generation
• Build and operate the training infrastructure by using containerized deployments and cloud GPU provisioning
• Ship models to production with cloud and edge inference and build the evaluation harness to guarantee safe deployments
• Create and maintain internal data quality and inspection tooling

• 5+ years of experience in a professional SWE environment building production software with a significant focus on data platforms or ML infrastructure
• Strong Python knowledge and comfortable in a typed language (Rust, Go, C++, ...)
• Experience in data pipelines and storage: tiered architecture, workflow orchestration, backfills, and schema evolution
• Cloud training experience: you have provisioned GPU instances and trained in a reproducible setup, from containerized deployments to a model registry
• Hands-on ML experience: you have trained models and understand dataloader throughput, GPU utilization, and can debug slow or stalled training runs
• Strong SWE foundations: You work with IaC and code reviews, propose architectural changes and refactors, and build internal tooling and automation

These skills are a plus:

• Edge inference deployment (Jetson or similar) with TensorRT, ONNX, quantization
• Multimodal and time-series data: video pipelines, sensor logs, MCAP, time alignment across sources
• Distributed training and training performance optimization
• GPU cluster management and job orchestration
• Rust in production