AI/ML Ops Engineer

As an AI/ML Engineer at Automation Anywhere, you will play a crucial role in optimizing cloud infrastructure management and operational efficiency through the design, development, and deployment of machine learning models and AI algorithms. Your responsibilities will include: - Designing, developing, and deploying AI/ML models to automate cloud infrastructure, monitoring, fault detection, and predictive maintenance. - Collaborating with Cloud Engineers, ML Engineers, Data Scientists, and DevOps teams to integrate AI/ML solutions into cloud orchestration and management platforms. - Building scalable data pipelines and workflows using cloud-native services for real-time and batch ML model training and inference. - Analyzing large volumes of cloud telemetry data to extract actionable insights using statistical methods and ML techniques. - Implementing anomaly detection, capacity forecasting, resource optimization, and automated remediation solutions. - Developing APIs and microservices to expose AI/ML capabilities for CloudOps automation. - Working with SecOps to ensure ML models comply with privacy and governance standards. - Optimizing existing AI/ML workflows for cost, performance, and accuracy. - Staying updated with the latest trends in AI/ML, cloud computing, and infrastructure automation. Qualifications and Requirements: - 6+ years of professional experience in AI/ML engineering, preferably in cloud infrastructure or operations environments. - Strong proficiency in Python or R, relevant libraries such as pandas and numpy. - Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, scikit-learn. - Experience with MCP Server, AI Agents, and A2A communication. - Expertise in cloud platforms (AWS, Azure, GCP) and their AI/ML services. - Strong understanding of data structures, algorithms, and statistical modeling. - Experience building and maintaining data pipelines using tools like Apache Spark, Kafka, Airflow. - Knowledge of containerization and orchestration (Docker, Kubernetes) to deploy ML models in production. - Familiarity with infrastructure monitoring tools and cloud management platforms. - Experience with CI/CD pipelines and automation tools in cloud environments. - Excellent problem-solving skills and ability to work independently and in cross-functional teams. - Strong communication skills for collaborating with technical and non-technical stakeholders. - Knowledge of Infrastructure as Code (IaC) tools like Terraform, CloudFormation. - Experience with cybersecurity principles related to cloud and AI/ML systems. Please note that all unsolicited resumes submitted to any @automationanywhere.com email address will not be eligible for an agency fee.,