Senior MLOps Engineer

We are seeking a Senior MLOps Engineer to join our dynamic team in Karnataka. The ideal candidate will have a strong background in machine learning operations and cloud technologies, particularly with Google Cloud Platform (GCP) and its suite of tools. This role is pivotal in bridging the gap between data science and operations, ensuring that machine learning models are efficiently deployed and maintained in production environments. Key Responsibilities: - Design, implement, and manage MLOps pipelines using tools such as Vertex AI, Kubeflow, and Vertex Pipelines. - Collaborate with data scientists to operationalize machine learning models and ensure their scalability and reliability. - Utilize Generative AI technologies and frameworks like Gemini and Agent Builder to enhance model performance and capabilities. - Implement CI/CD practices for machine learning workflows to streamline deployment processes. - Manage containerized applications using Docker and Kubernetes, ensuring seamless integration and orchestration in GKE. - Conduct performance monitoring and optimization of deployed models, utilizing tools like BigQuery and SQL for data analysis. - Stay updated with the latest advancements in MLOps and cloud technologies to continuously improve our processes. Required Skills: - Proficiency in GCP and its machine learning services, particularly Vertex AI. - Strong experience with MLOps practices and tools, including Kubeflow and Vertex Pipelines. - Solid programming skills in Python, with experience in SQL for data manipulation. - Familiarity with containerization technologies such as Docker and orchestration tools like Kubernetes. - Knowledge of CI/CD methodologies and tools, as well as infrastructure as code using Terraform. - Understanding of Generative AI concepts and applications. If you are passionate about leveraging machine learning in production and have the skills to drive MLOps initiatives, we encourage you to apply for this exciting opportunity.