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Senior AI Infrastructure Engineer; Zürich

Job in Zürich, 8081, Zurich, Kanton Zürich, Switzerland
Listing for: Loki Robotics
Full Time position
Listed on 2026-08-25
Job specializations:
  • Software Development
    Data Engineering, Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 140000 - 210000 CHF Yearly CHF 140000.00 210000.00 YEAR
Job Description & How to Apply Below
Position: Senior AI Infrastructure Engineer (Zürich, 100%)
Location: Zürich

We are hiring a AI Infrastructure Engineer

Start date:

ASAP

Zürich, Switzerland (on-site, remote not possible)

Full-time (100%)

Your role

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

What you should have:

  • 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

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

Don't worry if you don't hit every check-mark. We value people who learn fast and care about building great products.

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Position Requirements
10+ Years work experience
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