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Verified Job Engineering - Architecture

Artificial Intelligence Engineer (Visakhapatnam)

Jaipur, Rajasthan
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Engineering - Architecture
#733190
Remote / WFH
Pearson

Job Description

Job Summary We are looking for a highly skilled and experienced AI Engineer with strong expertise in Machine Learning, Generative AI, MLOps, and CI/CD automation using Jenkins. The ideal candidate will be responsible for designing, developing, deploying, and maintaining scalable AI/ML solutions while implementing robust automation pipelines for model training, testing, deployment, and monitoring. This role requires close collaboration with Data Scientists, DevOps Engineers, Software Developers, and Cloud teams to operationalize AI models in production environments. Key Responsibilities AI/ML Development - Design, develop, and deploy machine learning and AI solutions for business applications. - Build scalable AI systems using Python and contemporary AI/ML frameworks. - Develop and optimize NLP, Computer Vision, Recommendation Systems, Predictive Analytics, or Generative AI applications. - Work with LLMs, prompt engineering, embeddings, vector databases, and RAG architectures where applicable. - Fine-tune and evaluate machine learning models for performance, scalability, and accuracy. MLOps & Automation - Build and maintain end-to-end MLOps pipelines for model training, validation, deployment, and monitoring. - Implement CI/CD pipelines using Jenkins for automated build, testing, and deployment of AI applications. - Automate model lifecycle management including versioning, retraining, rollback, and monitoring. - Integrate Jenkins with Git, Docker, Kubernetes, Terraform, and cloud-native deployment tools. - Ensure reproducibility and reliability of AI workflows. Cloud & Infrastructure - Deploy AI/ML workloads on cloud platforms such as AWS, Azure, or GCP. - Manage containerized AI applications using Docker and Kubernetes. - Work with infrastructure-as-code and orchestration tools. - Optimize GPU/compute resource utilization for training and inference workloads. Data Engineering & Integration - Collaborate with data teams to prepare and process structured/unstructured dat
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