Location: Woonsocket, RI
Duration: 6 months
Experience Required
6–8 years of overall experience in software development, data analytics, or data science
2+ years of hands-on experience with deep learning, NLP, and Generative AI
Responsibilities
Design, build, fine-tune, and deploy LLM-based applications using Python
Implement and optimize deep learning models for NLP use cases, including text classification, sentiment analysis, and text summarization
Develop solutions using prompt engineering techniques
Utilize vector databases to store and retrieve model embeddings and AI-generated data
Work with deep learning frameworks and libraries such as TensorFlow, PyTorch, and Hugging Face Transformers
Apply knowledge of deep learning architectures and techniques
Use orchestration frameworks such as LangChain or similar tools
Build AI-powered applications using Streamlit, FastAPI, and Flask
Deploy and scale machine learning models on Azure and Google Cloud Platform (GCP)
Write efficient, well-documented, and maintainable Python code
Support CI/CD pipelines for ML and GenAI deployments
Apply knowledge of agentic architectures and multi-agent patterns such as AutoGen or similar frameworks
Collaborate with cross-functional teams to design scalable AI systems
Required Skills
6–8 years of overall experience in software development, data analytics, or data science
2+ years of hands-on experience with deep learning, NLP, and Generative AI
Strong proficiency in Python
Experience in deep learning, Natural Language Processing (NLP), and Generative AI
Understanding of large language models and their real-world applications
Experience managing AI model lifecycle from development to production
Experience deploying AI solutions on Azure or GCP
Knowledge of healthcare domain workflows and data
Familiarity with agentic and multi-agent AI design patterns
GCP
CI/CD
Skills: Digital : Python ~ Digital : Natural Language Processing (NLP)