An international SaaS company with a strong focus on AI-driven enterprise solutions is expanding its R&D presence in Europe. The company builds large-scale cloud and AI platforms for global clients across professional services, finance, and consulting industries.

As an MLOps Engineer, you’ll play a key role in bridging data science and engineering teams, ensuring smooth model deployment, scalability, and automation. You’ll design, build, and maintain robust ML infrastructure and pipelines in a modern cloud environment.

• Collaborate with data scientists and engineers to design and implement scalable MLOps workflows;


• Build and maintain automated pipelines for data processing, model training, validation, deployment, and monitoring;


• Develop and manage cloud-based infrastructure for ML workloads;


• Implement observability systems for model drift, data quality, and performance tracking;


• Promote and enforce best practices in MLOps, DevOps, and model governance;


• Mentor team members and contribute to establishing a strong engineering culture.

Nice to Have

• Experience with Spark, Databricks, or similar big data processing frameworks;


• Familiarity with model registry systems (MLflow, Vertex AI, SageMaker);


• Knowledge of Python and ML frameworks (scikit-learn, TensorFlow, PyTorch);


• Background in Generative AI or LLM fine-tuning pipelines;


• Contributions to open-source MLOps or DevOps tools.

• 4+ years of hands-on experience in MLOps, Data Engineering, or DevOps;


• Strong understanding of machine learning lifecycle and concepts;


• Solid experience with cloud platforms (Azure, AWS, or GCP);


• Proficiency in containerization and orchestration (Docker, Kubernetes);


• Experience with CI/CD tools such as Jenkins, Airflow, or Azure DevOps;


• Familiarity with monitoring, observability, and model performance tracking;


• Excellent communication and collaboration skills.

• Full CET overlap.


• Locations: Only Serbia, Portugal, Poland, Croatia.