Generative AI Developer

at  Capgemini

SOFT SKILLS:

Work Underpressure, Quality at work, Results Oriented

What can YOU expect in a career with Capgemini?

• Working in a team environment, Consultants will focus on the analysis, design and development of technology-based solutions for Capgemini’s clients.
• You will work alongside technical, functional and industry specialists to assist with the development, implementation and integration of innovative system solutions including methods, techniques and tools.
• You will contribute to client satisfaction by providing timely and responsive value-added services and work products.
• Capgemini offers a competitive compensation and benefits package.
• Headquartered in Paris, France, Capgemini has a presence of more than 340 thousand professionals in Mexico distributed among 3 sites located in Mexico City, Monterrey and Aguascalientes. A deeply multicultural organization.
• Capgemini has developed its own way of working, the Collaborative Business ExperienceTM, and draws on Rightshore, its worldwide delivery model.

• Design and implement generative AI models using frameworks such as TensorFlow, PyTorch, or JAX.
• Work with advanced machine learning techniques, including GANs, VAEs (Variational Autoencoders), and transformer-based models.
• Stay up to date with the latest advancements in generative AI and apply cutting-edge research to develop innovative products.
• Collaborate with other research teams to explore new applications and technologies within the field of AI.
• Improve the efficiency and accuracy of generative models, implementing optimization techniques such as pruning, quantization, and knowledge distillation.
• Ensure the scalability of models for deployment in production environments.
• Work closely with software development teams, data scientists, and designers to integrate generative AI models into commercial applications and end-user products.
• Contribute to the definition of model architecture and the end-to-end lifecycle of AI solutions.
• Develop solutions to process and generate relevant outputs from large datasets using advanced data processing and machine learning techniques.
• Ensure that data pipelines and models are efficient and capable of handling real-world datasets at scale.
• Contribute to the development of generative AI-powered products such as content generation tools for text, images, video, music, or other multimedia.
• Provide insights into the application of generative models for commercial use cases.
• Implement rigorous testing strategies to ensure the robustness, reliability, and ethical considerations of generative models.
• Evaluate model performance, identify limitations, and propose improvements.