Job Overview:We are looking for an experienced MLOps Engineer with 5+ years of expertise to join our team on a full-time basis.

The successful candidate will work with a cutting-edge stack to manage and optimize machine learning pipelines, ensuring efficient deployment, monitoring, and scalability.

This role will be entirely remote, and a high proficiency in English (C1) is required.Key Responsibilities:ML Pipeline Management: Design, build, and maintain machine learning pipelines using Azure, Azure ML, and other cloud technologies.Integration and Automation: Implement and optimize workflows using tools like Kedro, Promptflow, and Airflow for seamless integration and automation.Model Deployment & Monitoring: Ensure efficient deployment of machine learning models with tools like FastAPI and monitor model performance using Elasticsearch.Collaboration: Work closely with data scientists and engineers to streamline the development-to-production process, integrating DSPy and Python-based solutions.Performance Optimization: Continuously monitor, troubleshoot, and improve ML models' performance, scaling the architecture as needed.Tech Stack:Cloud: Azure, Azure MLWorkflow Orchestration: Kedro, Promptflow, AirflowProgramming: Python, DSPyAPIs & Frameworks: FastAPIMonitoring & Search: ElasticsearchQualifications:Experience: 5+ years of experience in MLOps and machine learning pipeline management.Cloud Expertise: Strong hands-on experience with Azure and Azure ML.Automation & Orchestration Tools: Proven experience with Kedro, Promptflow, and Airflow.Programming: Proficiency in Python and related tools (DSPy).API Integration: Experience with deploying APIs using FastAPI.Monitoring Tools: Strong knowledge of Elasticsearch for monitoring and troubleshooting