Akvelon

Compensation

Full Description

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. Tasks 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. Requirements 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. Benefits Full CET overlap. Locations: Only Serbia, Portugal, Poland, Croatia.