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# AI/ML, GenAI & Python Developer - Onsite NJ

- **Company:** Capgemini
- **Location:** United States
- **Salary:** $106,230.0 - $145,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Python (Programming Language), Search Algorithms, Machine Learning, Natural Language Processing, Performance Tuning, Scrum Methodology, Tensorflow, Search Technologies, Data Processing, Enterprise Software Applications, Pytorch, Large Language Models, Prompt Engineering, Deep Learning, Model Validation, Generative AI, Keras, Git, Fastapi, Kubernetes, HuggingFace, Machine Learning Operations, Virtual Agents, Restful APIs, Streamlit Framework, Docker, Databricks
- **Published:** July 28, 2026
- **Apply:** https://www.capgemini.com/jobs/525574-en_US_SAPBTP/x/

## About the Role

Required Skills: Python, Machine Learning, Deep Learning, PyTorch, TensorFlow, Keras, Generative AI, Large Language Models (LLMs), Prompt Engineering, Fine-Tuning Techniques (LoRA, QLoRA), Hugging Face, LangChain, LlamaIndex, Retrieval-Augmented Generation (RAG), Vector Databases, Hybrid Search Techniques, NLP, Data Processing, REST APIs, Git, Agile/Scrum.

Preferred Skills: Agentic AI Frameworks, AI Model Evaluation, MLOps, Azure OpenAI, AWS Bedrock, Databricks, Streamlit, FastAPI, Docker, Kubernetes, Banking or Financial Services Domain Experience.

## Description

Design, develop, and deploy AI/ML and Generative AI solutions using Python, build and fine-tune machine learning and large language models using frameworks such as PyTorch, TensorFlow, and Keras, develop RAG-based applications using LangChain, Hugging Face, and LlamaIndex, implement and optimize vector search and hybrid search solutions, perform model training, evaluation, and fine-tuning using techniques such as LoRA and QLoRA, develop APIs and AI-powered services, integrate AI models with enterprise applications, ensure model performance, scalability, and reliability, collaborate with business and technology teams to translate requirements into AI solutions, and participate in Agile development, testing, deployment, and support activities.


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