Senior AI Infrastructure Engineer (Zürich, 100%)

Nabla; Zürich; Vor Ort; CHF 140.000 - 190.000; Vollzeit

Zusammenfassung

Nabla is seeking a Senior AI Infrastructure Engineer in Zürich to design and operate the data and training platforms powering our robot learning.

You will build data processing pipelines, deployment tooling, and scalable ML infrastructure, collaborating across data, tooling, and MLOps teams to enable end‑to‑end model development and production workflows.

Qualifikationen

• 5+ years of experience in a professional SWE environment with focus on data platforms or ML infrastructure.
• Strong Python knowledge and comfort with typed languages (Rust, Go, C++, …).
• Experience in data pipelines and storage: tiered architectures, orchestration, backfills, and schema evolution.
• Cloud training experience: provisioned GPU instances, reproducible setups, containerized deployments to model registry.
• Hands‑on ML experience: trained models, dataloader throughput, GPU utilization, debugging long training runs.
• Strong SWE foundations: IaC, code reviews, architecture refactors, internal tooling.

Aufgaben

• Build a tiered data processing platform from ingestion to versioned training data.
• Operate training infrastructure with containerized deployments and cloud GPU provisioning.
• Ship models to production with cloud and edge inference and build evaluation harnesses.
• Create and maintain internal data quality and inspection tooling.

Kenntnisse

Python

Rust

Go

C++

Data pipelines

IaC

Model deployment

Experimentation

Tools

TensorRT

ONNX

Kubernetes

Docker

GPU provisioning

Jobbeschreibung

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 Engineer

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.

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 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

Interested?

Shoot us a message to [e-mail], 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.