.**RH**:Raul García**Position**:Generative AI Developer**Location**:Aguascalientes, Mexico**Industry - Sector**:MALS**What you'll do?**- 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.- 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.- 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.- Implement rigorous testing strategies to ensure the robustness, reliability, and ethical considerations of generative models.- Evaluate model performance, identify limitations, and propose improvements.**What you'll bring**:- Proficiency in Python and familiarity with programming languages such as C++ or Java for optimization tasks.- Extensive experience with deep learning frameworks like TensorFlow, PyTorch, or JAX for developing and training generative models.- Expertise in designing and deploying Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformer-based models such as GPT, BERT, or similar architectures.- Strong knowledge of linear algebra, probability theory, statistics, and optimization techniques relevant to AI and machine learning.- Experience in handling large datasets, including preprocessing, augmentation, and cleaning data for AI models.- Familiarity with data pipeline tools like Apache Spark, Dask, or similar technologies for scalable data processing.- Knowledge of cloud platforms (AWS, Google Cloud, Azure) and experience in deploying machine learning models in cloud environments.- Strong software engineering skills, including version control (Git), collaborative workflows, and Agile methodologies.- Performance Tuning & Model Optimization:- Experience with model optimization techniques such as pruning, quantization, and distributed training for large-scale model deployment.- Understanding of the ethical considerations in AI development, including fairness, transparency, and bias mitigation techniques.**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