Requirements:

• Proficiency with Python (3+ years of experience);
• Solid experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, Airflow, AWS SageMaker, Azure ML);
• Experience deploying ML models to cloud environments (GCP, AWS, Azure);
• Familiarity with containerization and orchestration technologies (Docker, Kubernetes);
• Practical experience with automation, CI/CD, and DevOps principles;
• Good understanding of machine learning models, especially NLP models like transformers;
• English proficiency at B2 level or above.

It will be a plus:

• Familiarity with ONNX, TensorRT, OpenVINO;
• Experience optimizing ML model inference speed and efficiency;
• Fundamental understanding of networking and distributed computing;
• Experience working with multimodal machine learning systems;
• Interest in open-source contributions.