Executive - Dev - cloud, java, full stack

Role Overview: As an AI/ML Engineer at KPMG in India, your primary responsibility will be to deploy, manage, and optimize AI/ML models in production environments. You will collaborate with data scientists, software engineers, and IT teams to ensure seamless integration and operation of AI/ML solutions. Your role is crucial in operationalizing AI models to ensure scalability, reliability, and value delivery to the business. Key Responsibilities: - Design, implement, and maintain end-to-end MLOps pipelines for deploying machine learning models into production. - Collaborate with data scientists to understand model requirements and ensure smooth deployment and integration. - Develop and manage infrastructure for model training, validation, deployment, monitoring, and retraining. - Implement CI/CD pipelines to streamline the deployment and updates of AI/ML models. - Ensure scalability, reliability, and performance of deployed models through continuous monitoring and optimization. - Utilize containerization and orchestration tools (e.g., Docker, Kubernetes) for managing model deployment environments. - Work with cloud platforms (AWS, GCP, Azure) to deploy and manage AI/ML services. - Implement security best practices for AI/ML models and data pipelines. - Troubleshoot and resolve issues related to model deployment and operation. - Stay updated with the latest MLOps tools, frameworks, and methodologies. - Document processes, configurations, and procedures for knowledge sharing and continuity. Qualifications Required: - Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field. - Proven experience (3-5 years) in deploying machine learning models in production environments. - Strong understanding of machine learning, deep learning, NLP, and generative AI techniques. - Proficiency with MLOps tools and frameworks such as MLflow, Kubeflow, TensorFlow Extended (TFX), or similar. - Experience with CI/CD tools such as Jenkins, GitLab CI, or CircleCI. - Proficiency in programming languages such as Python and familiarity with ML/DL frameworks like TensorFlow, PyTorch, and scikit-learn. - Experience with cloud platforms (AWS, GCP, Azure) and their AI/ML services. - Knowledge of containerization and orchestration tools (Docker, Kubernetes). - Strong understanding of version control systems (e.g., Git) and collaborative development workflows. - Excellent problem-solving skills and ability to design robust, scalable MLOps solutions. - Strong communication skills for effective collaboration with cross-functional teams. (Note: Additional details about the company were not provided in the job description.),