AI Engineer

Role Overview: As an AI/ML Engineer, your role will involve designing, training, and deploying AI/ML models for enterprise use cases. You will be responsible for integrating AI models into enterprise applications using cloud-native architectures, implementing data pipelines, feature engineering, and model evaluation frameworks. Additionally, you will optimize models for performance, scalability, and cost-efficiency while ensuring security, compliance, and governance in AI solutions. Your role will also include training and mentoring team members on AI/ML concepts, tools, and best practices, as well as collaborating with product and engineering teams to deliver AI-driven features. Key Responsibilities: - Design, train, and deploy AI/ML models for enterprise use cases - Integrate AI models into enterprise applications using cloud-native architectures - Implement data pipelines, feature engineering, and model evaluation frameworks - Optimize models for performance, scalability, and cost-efficiency - Ensure security, compliance, and governance in AI solutions - Train and mentor team members on AI/ML concepts, tools, and best practices - Collaborate with product and engineering teams to deliver AI-driven features Qualifications Required: - 5 years of experience in enterprise software development with strong coding skills (e.g., Python, .NET, or Java) - 2 years of experience in ML/AI, including model training, evaluation, and deployment - Hands-on experience with enterprise cloud platforms such as Azure, AWS, or GCP, and relevant AI services - Proven experience in at least one end-to-end AI project involving offline model deployment - Strong understanding of data preprocessing, feature engineering, and model optimization - Familiarity with MLOps practices, including CI/CD for ML, model versioning, monitoring,