Data Scientist

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior AI/ML Engineer focused on NLP and Generative AI, offering a 6-month hybrid contract in Malvern, PA. Requires 10+ years in IT, 4-5+ years in ML, AWS expertise, and proficiency in Python and MLOps practices.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
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πŸ—“οΈ - Date discovered
August 6, 2025
πŸ•’ - Project duration
More than 6 months
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🏝️ - Location type
Hybrid
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πŸ“„ - Contract type
Unknown
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πŸ”’ - Security clearance
Unknown
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πŸ“ - Location detailed
Malvern, PA
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🧠 - Skills detailed
#AWS (Amazon Web Services) #ML (Machine Learning) #Scala #SageMaker #A/B Testing #Databases #NLP (Natural Language Processing) #Kafka (Apache Kafka) #Monitoring #Cloud #"ETL (Extract #Transform #Load)" #AWS Kinesis #Computer Science #Data Processing #AI (Artificial Intelligence) #Transformers #DynamoDB #Langchain #Athena #Python #OpenSearch #Data Science #PyTorch #AutoScaling #Lambda (AWS Lambda) #Classification #NLG (Natural Language Generation)
Role description
Job Title: Senior AI/ML Engineer – NLP, Generative AI, AWS Location: Malvern, PA (Hybrid)- 6 months contract can be extended to a year About the Role: 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: β€’ Design, develop, and deploy intent classification and intent detection models using LLMs and traditional NLP methods β€’ Build and optimize Natural Language Generation (NLG) pipelines for chatbot responses, summarization, content creation, or knowledge grounding β€’ Architect and implement LangChain and LangGraph based applications for LLM-driven workflows (e.g., autonomous agents, RAG systems) β€’ Develop scalable machine learning pipelines using the AWS tech stack (e.g., Sagemaker, Lambda, Bedrock, Step Functions, DynamoDB, Athena) β€’ Integrate and fine-tune foundation models via AWS Bedrock, including Amazon Titan, Anthropic Claude, or Meta Llama β€’ Collaborate closely with product managers, ML researchers, and backend engineers to translate business requirements into robust AI solutions β€’ Lead experimentation efforts, conduct A/B testing, and ensure continuous evaluation of deployed ML models β€’ Mentor junior ML engineers and contribute to best practices in MLOps, model governance, and responsible AI Required Qualifications: β€’ Total 10+ years in IT with 4 to 5+ years of experience in machine learning, with a focus on NLP and Generative AI β€’ Strong experience building and deploying intent detection, text classification, sequence tagging, and entity recognition models β€’ Proficient in LangChain, LangGraph, vector databases (e.g., FAISS, Pinecone), and orchestration of LLM workflows β€’ Deep knowledge of AWS Bedrock, Amazon SageMaker, Lambda, DynamoDB, Step Functions, etc. β€’ Experience working with open-source LLMs (LLaMA, Mistral, Falcon) or commercial APIs (Claude, GPT-4, etc.) β€’ Proficient in Python, with a solid grasp of ML frameworks such as PyTorch, HuggingFace Transformers, scikit-learn β€’ Strong understanding of MLOps practices including model versioning, CI/CD for ML, monitoring, and auto-scaling β€’ Bachelor’s or Master’s in Computer Science, Data Science, or a related field Nice to Have: β€’ Experience integrating RAG (Retrieval-Augmented Generation) systems at scale β€’ Familiarity with vector search using Amazon OpenSearch, Pinecone, or Weaviate β€’ Experience with streaming data processing (e.g., AWS Kinesis, Kafka) β€’ Contributions to open-source AI/ML or NLP projects