Role Name: Senior AI/ML Engineer Location: Malvern, PA

Duration: Months

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 (, autonomous agents, RAG systems).

• Develop scalable machine learning pipelines using the AWS tech stack (, 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 + in IT with to + 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 (, 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-, 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 (, AWS Kinesis, Kafka).

• Contributions to open-source AI/ML or NLP projects.