Description
You will build and deploy intent classification, entity recognition, and text generation models.
Responsibilities
- Architect LangChain/LangGraph workflows for autonomous agents and RAG systems.
- Develop scalable ML pipelines using AWS SageMaker, Lambda, Bedrock, Step Functions, DynamoDB, Athena.
- Fine-tune and integrate foundation models (Claude, LLaMA, Titan, GPT-4, etc.) via AWS Bedrock.
- Lead experimentation, A/B testing, and model evaluation.
- Mentor junior engineers and establish best practices in MLOps and responsible AI.
Required Skills
- 7+ years in ML with focus on NLP & Generative AI.
- Proficiency in Python, PyTorch, HuggingFace, sci-kit-learn.
- Strong expertise in LangChain, LangGraph, vector databases (FAISS, Pinecone).
- Deep knowledge of AWS Bedrock & cloud-native ML architecture.
- Experience with AWS SageMaker, Lambda, Bedrock.
- Experience with NLP and Generative AI models.
Preferred Skills
- RAG systems and vector search implementation.
- Experience with streaming data.