AI Engineer (Enterprise Cloud ML/AI)

ROLES AND RESPONSIBILITY

• Design, train, and deploy AI/ML models, including offline deployment 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.
  

DESIRED SKILLS

• 5 years in enterprise software development with strong coding skills (e.g., Python, .NET, or Java).
• 2 years in ML/AI: 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: CI/CD for ML, model versioning, monitoring.
  

GOOD TO HAVE

• Experience with Azure AI Services, Azure ML, or equivalent cloud AI platforms.
• Knowledge of vector databases, RAG architectures, and LLM integration.
• Familiarity with containerization (Docker, Kubernetes) and IaC (Terraform/Bicep).
• Exposure to Responsible AI principles and compliance frameworks.
  

TOOLS & TECHNOLOGIES

• ML/AI: TensorFlow, PyTorch, Scikit-learn, ONNX.
• Cloud: Azure ML, AWS SageMaker, GCP Vertex AI.
• DevOps/MLOps: GitHub Actions, Azure DevOps, MLflow, Kubeflow.
• Data: SQL/NoSQL databases, Data Lakes, Feature Stores.
  

EDUCATION

• BE/BTech/MCA or equivalent in Computer Science or related field.
  

WORK LOCATION

• Full-time position based in Raipur & Pune.