AI/ML Engineer
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AI/ML Engineer2
Key Responsibilities
- Build and deploy LLM-based GenAI applications end-to-end
- Work with multiple LLMs (OpenAI/Azure OpenAI, Gemini, Claude, LLaMA, Mistral)
- Design and implement agentic and multi-agent systems using MCP and A2A
- Develop RAG pipelines and document intelligence solutions
- Use modern GenAI frameworks (LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, Google ADK)
- Build AI backend services using FastAPI and Flask
- Develop and integrate chat UIs, copilots, and dashboards with AI APIs
- Productionize, deploy, and monitor AI systems on cloud platforms
- Ensure performance, security, scalability, and Responsible AI compliance
Required Skills
- Strong Python programming with FastAPI and Flask
- Solid understanding of ML, Deep Learning, NLP, and GenAI concepts
- Hands-on experience with LLMs, embeddings, and prompt engineering
- Experience designing agentic systems with MCP / A2A
- Expertise in RAG architectures and vector databases (FAISS, Pinecone, Weaviate, Chroma, Milvus)
- Working knowledge of front-end technologies: HTML, CSS, JavaScript, Stremlit; React preferred
- API design and integration (REST / WebSockets)
- Strong deployment & MLOps experience: Azure / AWS / GCP, Docker, Kubernetes, CI/CD, MLflow / Azure ML / SageMaker / Vertex AI
Good to Have
- Fine-tuning open-source LLMs (LoRA, PEFT, Hugging Face)
- Experience with autonomous agents and async workflows
- Exposure to RPA + Agentic AI integration
- Knowledge of AI governance, monitoring, and security
Skills
- Agentic AI
- AI
- API
- Api Design
- AutoGen
- AWS
- Azure
- CI/CD
- Cloud
- CrewAI
- CSS
- Deep Learning
- Docker
- Embeddings
- FAISS
- FastAPI
- Fine Tuning
- Flask
- GCP
- Generative AI
- HTML
- Hugging Face
- JavaScript
- Kubernetes
- LangChain
- LangGraph
- LlamaIndex
- LLM
- Machine Learning
- MCP
- Milvus
- Mistral
- MLflow
- MLOps
- NLP
- OpenAI
- PEFT
- Pinecone
- Prompt Engineering
- Python
- RAG
- React
- RPA
- SageMaker
- Vector Databases
- Vertex AI
- Weaviate
- Websockets