Lead AIML engineer
Tasks
- Build knowledge management solutions
- Build predictive and classification models
- Build recommendation and forecasting models
- Build scalable AI applications
- Design AI and machine learning solutions
- Develop AI agents
- Develop AI applications with Python
- Develop AI assistants and chatbots
- Develop generative AI solutions
- Evaluate AI models and platforms
- Implement AI application architecture best practices
- Implement CI/CD pipelines for models
- Implement MLOps model versioning
- Implement retrieval-augmented generation
- Lead AI and machine learning deployments
- Manage AI model lifecycle
- Monitor models in production
- Perform generative AI knowledge retrieval
- Provide technical mentorship
- Work with vector databases
Perks/Benefits
- Career growth opportunities
- Educational reimbursement
- Flexibility and autonomy
- Training and development
Skills/Tech-stack
AI Agents | AI Search | APIs | AWS | Azure AI | Azure AI Search | CI/CD | ChromaDB | Cloud platform | Conversational AI | Docker | Faiss | Generative AI | Google Cloud | Google Cloud Platform | Kubernetes | Langchain | Language Models | Large Language Models | Llamaindex | MLOps | Microservices Architecture | Microsoft Azure | Model Governance | Model Monitoring | Pinecone | Prompt engineering | PyTorch | Python | Retrieval-Augmented Generation | Scikit-learn | Semantic Kernel | TensorFlow | Vector Databases | Weaviate | XGBoost
Education
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer | Software Engineer
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