AI/ML Engineer

Lead AI/ML Engineer – NLP & LLM Malvern,PA(Onsite) Contract JOB DESCRIPTION: We are seeking a highly experienced Senior AI/ML Engineer with deep expertise in Natural Language Processing (NLP), Generative AI, and cloud-native ML systems. This role is ideal for someone who has built production-ready intent detection models, NLG systems, and has strong experience with AWS Bedrock, LangChain, and LangGraph. You’ll play a key role in architecting and scaling AI-first applications that leverage the latest in LLM, orchestration, and AWS-native services. Key Responsibilities: • Design, develop, and deploy intent classification and intent detection models using LLMs and traditional NLP methods. • Build and optimize Natural Language Generation (NLG) pipelines for chatbot responses, summarization, content creation, or knowledge grounding. • Architect and implement LangChain and LangGraph based applications for LLM-driven workflows (e.g., autonomous agents, RAG systems). • Develop scalable machine learning pipelines using the AWS tech stack (e.g., Sagemaker, Lambda, Bedrock, Step Functions, DynamoDB, Athena). • Integrate and fine-tune foundation models via AWS Bedrock, including Amazon Titan, Anthropic Claude, or Meta Llama. • Collaborate closely with product managers, ML researchers, and backend engineers to translate business requirements into robust AI solutions. • Lead experimentation efforts, conduct A/B testing, and ensure continuous evaluation of deployed ML models. • Mentor junior ML engineers and contribute to best practices in MLOps, model governance, and responsible AI. Required Qualifications: • Total 4 to 5 + years of experience in machine learning, with a focus on NLP and Generative AI. • Strong experience building and deploying intent detection, text classification, sequence tagging, and entity recognition models. • Proficient in LangChain, LangGraph, vector databases (e.g., FAISS, Pinecone), and orchestration of LLM workflows. • Deep knowledge of AWS Bedrock, Amazon SageMaker, Lambda, DynamoDB, Step Functions, etc. • Experience working with open-source LLMs (LLaMA, Mistral, Falcon) or commercial APIs (Claude, GPT-4, etc.). • Proficient in Python, with a solid grasp of ML frameworks such as PyTorch, HuggingFace Transformers, scikit-learn. • Strong understanding of MLOps practices including model versioning, CI/CD for ML, monitoring, and auto-scaling. • Bachelor’s or Master’s in Computer Science, Data Science, or a related field. Nice to Have: • Experience integrating RAG (Retrieval-Augmented Generation) systems at scale. • Familiarity with vector search using Amazon OpenSearch, Pinecone, or Weaviate. • Experience with streaming data processing (e.g., AWS Kinesis, Kafka). • Contributions to open-source AI/ML or NLP projects