Senior AI Platform Engineer (MLOps)

RetInSight GmbH; Wien; Hybrid; EUR 58.000 - 71.000; Vollzeit

Benefits dieser Stelle

Hybrid work model

Central Vienna office

Public transport support

Team events

Well-equipped kitchen

Zusammenfassung

RetInSight GmbH in Vienna is seeking a Senior AI Engineer to own and advance the shared infrastructure for AI development, experimentation and delivery. You will shape the platform architecture, ensure security, scalability and reliability, and work across AI, Data, Analysis and Software teams.

The role demands deep ML engineering expertise, platform-minded thinking, and the ability to align technical stakeholders while contributing hands-on to model integration when needed.

Qualifikationen

• Bachelor's or Master's degree in computer science, engineering or related field or equivalent experience.
• 5+ years of ML engineering, platform engineering or MLOps with production AI systems.
• Expert Python and software engineering skills (modular architecture, APIs, testing, async processing).
• Strong experience with Docker, CI/CD, cloud platforms, orchestration, experiment tracking, model registries, observability and IaC.

Aufgaben

• Own architecture, roadmap and continuous improvement of shared tool stack for AI development, experimentation and delivery.
• Maintain reliability, usability, security and scalability of the platform and its core services.
• Design reusable services, APIs, interfaces and automation for experimentation, evaluation, data processing and inference.

Kenntnisse

Python

MLOps

Docker

CI/CD

APIs

Observability

Cloud platforms

PyTorch

GPU workloads

Ausbildung

Bachelor's or Master's in CS/Engineering

Tools

MCP servers

Experiment tracking

Model registries

Jobbeschreibung

RetInSight GmbH in Vienna is seeking a Senior AI Engineer to own and advance the shared infrastructure for AI development, experimentation and delivery. You will shape the platform architecture, ensure security, scalability and reliability, and work across AI, Data, Analysis and Software teams.

The role demands deep ML engineering expertise, platform-minded thinking, and the ability to align technical stakeholders while contributing hands-on to model integration when needed.