About the Company :Headquartered in California, U.S.A., GSPANN provides consulting and IT services to global clients. We help clients transform how they deliver business value by helping them optimize their IT capabilities, practices, and operations with our experience in retail, high-technology, and manufacturing. With five global delivery centers and 1900+ employees, we provide the intimacy of a boutique consultancy with the capabilities of a large IT services firm.Role: Azure ML EngineerExperinece:5+ yearsLocation: Gurgaon, Pune, Hyderabad, BangaloreTechnical Skill Requirements- MLOps, Python, Data Science, Databricks, AzureJob Summary:Design and implement MLOps pipelines for training, deployment, and monitoring of machine learning models.Build and maintain a scalable and reliable ML infrastructure using tools like Docker, Kubernetes, and cloud platforms like Azure, Databricks.Collaborate with data scientists and software engineers to ensure seamless integration of models into production environments.Develop and implement CI/CD pipelines for automated model training, testing, and deployment.Monitor model performance and implement alerting systems for drift and degradation.Champion best practices in MLOps and stay up-to-date with the latest advancements in the field.Identify opportunities to improve the efficiency, maintainability, and scalability of our ML systems.Benefits:Opportunity to work on cutting-edge machine learning projectsCollaborative and supportive work environmentBe a part of a team that is transforming the future!Required SkillsRelevant degree in Computer Science, Engineering, or a related field (or equivalent experience).5+ years of experience in software development or machine learning engineering.Proven experience in building and deploying machine learning models in production.Strong understanding of MLOps concepts and practices.Expertise in cloud platforms (AWS, GCP, Azure) is a plus.Must have knowledge on containerization technologies (Docker/Kubernetes).Must have CI/CD tools (GitLab CI, Jenkins, etc.).Must have ML model management tools (MLflow, Kubeflow, etc.).Proficiency in Python and familiarity with machine learning libraries (TensorFlow, PyTorch, etc.)Excellent communication, collaboration, and problem-solving skills.
