AI Engineer

As an AI/ML Engineer, your role involves designing, training, and deploying AI/ML models, with a focus on offline deployment for enterprise use cases. You will be responsible for integrating AI models into enterprise applications using cloud-native architectures. Additionally, you will implement data pipelines, conduct feature engineering, and develop model evaluation frameworks. Optimization of models for performance, scalability, and cost-efficiency will be a key part of your responsibilities. Ensuring security, compliance, and governance in AI solutions is crucial. Furthermore, you will play a significant role in training and mentoring team members on AI/ML concepts, tools, and best practices. Collaboration with product and engineering teams to deliver AI-driven features will also be part of your duties. 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 (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 such as CI/CD for ML, model versioning, and monitoring It is good to have experience with Azure AI Services, Azure ML, or equivalent cloud AI platforms. Knowledge of vector databases, RAG architectures, and LLM integration, as well as familiarity with containerization (Docker, Kubernetes) and IaC (Terraform/Bicep), are also beneficial. Exposure to Responsible AI principles and compliance frameworks is a plus. The tools and technologies you will work with include TensorFlow, PyTorch, Scikit-learn, ONNX for ML/AI, Azure ML, AWS SageMaker, GCP Vertex AI for cloud services, GitHub Actions, Azure DevOps, MLflow, Kubeflow for DevOps/MLOps, and SQL/NoSQL databases, Data Lakes, Feature Stores for data management. Your educational background should include a BE/BTech/MCA or equivalent in Computer Science or a related field. This full-time position is based in Raipur & Pune.,