Senior AI Infrastructure Engineer; Zürich
Listed on 2026-07-10
-
Software Development
Data Engineering, Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Location: Zürich
Senior AI Infrastructure Engineer (Zürich, 100%)
Start date:
ASAP
Zürich, Switzerland (on-site, remote not possible)
Full-time (100%)
We are hiring an AI Infrastructure EngineerAs 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.
Your roleAs 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 data loader 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
- 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
Shoot us a message to , including [AII] in the email subject.
Don’t worry if you don’t hit every check‑mark. We value people who learn fast and care about building great products. Just give it a go and apply.
#J-18808-LjbffrTo Search, View & Apply for jobs on this site that accept applications from your location or country, tap here to make a Search: