RealNetworks

We are looking for an DevOps Engineer with strong AWS, on-premise infrastructure, Linux, and automation experience. The ideal candidate also has Python experience and can support infrastructure for large machine learning models.

This role is embedded within the Data Science team and focuses on building, optimizing, and maintaining training, validation, data processing, and deployment workflows. The ideal candidate is a hands-on engineer who can help make ML development faster, more reliable, and more scalable across both local environments and AWS.

This is a hybrid role in Zagreb, Croatia. We are currently not open to B2B or fully remote collaboration for this role.

About us:
SAFR from RealNetworks is a unified ecosystem specializing in face-based computer vision solutions optimized for real-world performance. Building on a legacy of digital media expertise and innovation, RealNetworks has created a new generation of products that employ best-in-class artificial intelligence and machine learning to enhance and secure our daily lives.

Key Responsibilities:

• Build and maintain AWS and on-premise infrastructure.
• Manage Linux servers, services, containers, and deployment environments.
• Support infrastructure for large ML models, inference, and data processing workloads.
• Develop automation scripts and tools using Python and shell scripting.
• Maintain CI/CD pipelines and deployment workflows.
• Monitor systems, troubleshoot issues, and improve reliability.
   

Required Qualifications:

• 3+ years of experience in machine learning engineering, data engineering, DevOps, software engineering, or a related technical role.
• Bachelor’s degree in Engineering, Mathematics, Computer Science, Data Science, or a related field, or equivalent academic/practical experience.
• Strong DevOps and production infrastructure experience.
• Good knowledge of AWS and cloud services.
• Hands-on experience with on-premise infrastructure.
• Strong Linux experience.
• Python experience for scripting, automation, or tooling.
• Experience with CI/CD, Docker, networking, monitoring, and troubleshooting.
   

Preferred Qualifications:

• Experience with computer vision pipelines, including image or video data processing.
• Experience working with LLM applications, embeddings, retrieval-augmented generation, or LangChain-based workflows.
• Experience with large ML model infrastructure or ML pipelines.
• Experience with GPU servers or cloud GPU instances.
• Familiarity with Kubernetes and infrastructure-as-code tools.
• Experience with hybrid AWS/on-premise environments.
• Understanding of MLOps principles and production ML system design.

We look forward to meeting you!

Salary range for this position: $45,000-55,000