Machine Learning Engineer-Agentic AI
2 days ago
ML Engineer – Agentic AIResponsibilities- Design and implement multi-agent systems using LangChain, LangGraph, CrewAI, AutoGen or similar frameworks. - Build A2A (agent-to-agent) orchestration and implement MCP (multi-context protocol) for context reuse and collaboration. - Fine-tune foundation models (LoRA, RLHF, DPO) and integrate retrieval-augmented generation (RAG) pipelines. - Develop APIs and backend services (FastAPI/Flask/Node.js) and integrate with enterprise systems (HRIS, CRM, ERP). - Build secure data pipelines (ETL, embeddings, vector DB ingestion) and ensure governance, bias mitigation, and lineage. - Containerize, deploy, and monitor agents (Docker, Kubernetes, CI/CD pipelines) with observability and drift detection. - Collaborate with QA, red teaming, and product leads to benchmark accuracy, safety, and compliance.Skills Required- Strong in Python, PyTorch/TensorFlow, Hugging Face, and fine-tuning techniques (LoRA, RLHF). - Hands-on with LangChain/LangGraph, MCP, A2A orchestration, and multi-agent architectures. - Proficient in ETL pipelines, SQL/NoSQL, vector DBs (Pinecone, Weaviate, FAISS, Milvus). - Backend expertise in FastAPI/Flask/Node.js, REST/GraphQL APIs, and microservices. - DevOps/MLOps experience: Docker, Kubernetes, CI/CD (Jenkins/GitHub Actions), monitoring/observability. - Cloud experience with AWS/GCP/Azure AI services and secure integration practices. - Bonus: familiarity with enterprise HR/ATS systems (Workday, SAP, Paychex) and workflow automation.
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