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# Data Scientist

- **Company:** Capgemini
- **Location:** Irving, TX, United States
- **Experience:** Experienced
- **Salary:** $90,000.0 - $125,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Computer Vision, User Authentication, Cloud Computing, Information Engineering, Software Debugging, Hypertext Transfer Protocols (HTTP), JSON, Python (Programming Language), Machine Learning, Software Engineering, SQL Databases, Systems Integration, Large Language Models, Software Security, Model Validation, Generative AI, Rate Limiting, Information Technology, Machine Learning Operations, Stable Diffusion, Restful APIs, GPT, Web Api
- **Published:** August 9, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3343349930&tx=IT8477TTZ&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

Bachelor's degree or higher in AI, Machine Learning, Computer Science, or a related field.

3-5 years of experience in AI, Machine Learning, Data Science, or Application Development.

Experience deploying and managing production AI solutions with MLOps practices., A hands-on GenAI Engineer/Data Scientist with strong expertise in Generative AI, LLMs, AI agents, Python, SQL, cloud platforms, MLOps, APIs, and data engineering, capable of building and operating enterprise-scale AI solutions from development through production deployment.

## Description

The GenAI Engineer / Data Scientist role focuses on developing, deploying, and scaling Generative AI and Predictive AI solutions that drive business value. The position combines expertise in AI/ML, APIs, cloud platforms, data engineering, MLOps, and agentic AI workflows to build production-ready AI applications and automation solutions., AI & Machine Learning Development

Develop and deploy

Generative AI solutions (GPT, Claude, Stable Diffusion)

Predictive AI models (regression, classification, clustering)

NLP and Computer Vision applications

Build intelligent AI agents and agentic workflows to automate business processes.

Implement Retrieval-Augmented Generation (RAG) and multimodal AI solutions.

Application Architecture & API Integration

Design AI-enabled applications and integrations using:

REST APIs

JSON services

Authentication and Tokens

HTTP protocols and API endpoints

Handle API security, rate limiting, debugging, error handling, and documentation.

Model Deployment & MLOps

Deploy AI models into production environments.

Monitor model performance, scalability, and reliability.


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