Principal Fullstack AI/ML Consultant
Tasks
- Build AI deployment pipelines and automation frameworks
- Build RAG-based applications
- Design production grade AI and machine learning systems
- Design scalable cloud data and AI architectures
- Develop conversational AI assistants chatbots and agentic workflows
- Develop frontend and backend services and APIs
- Ensure security reliability performance and compliance across AI platforms
- Implement MLOps and LLMOps with monitoring evaluation and governance
- Provide post production support and optimize live solutions
- Translate requirements into AI solutions
Perks/Benefits
Skills/Tech-stack
AWS | Amazon Web Services | Automated testing | Cloud platform | Design Patterns | Docker | Function Calling | GCP | Google Cloud | Google Cloud Platform | JavaScript | Kubeflow | Kubernetes | LLMOps | Langchain | Langgraph | MLOps | MLflow | Microservices | Microsoft Azure | Model Evaluation | Model Governance | Monitoring | Observability | Prompt engineering | PyTorch | Python | RAG | Retrieval-Augmented Generation | Scikit-learn | Software Design | Software Design Patterns | Structured outputs | TensorFlow | Web Services | Workflow Orchestration
Education
N/A
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