Generative AI Engineer

Cognizant is seeking a talented Generative AI Engineer to join our team. This role is based in Hyderabad, Telangana, India, although the interview process may involve in-person modes.

About the Role

As a Generative AI Engineer, you will be instrumental in developing and deploying cutting-edge AI solutions. You will work with multimodal foundation models, develop and optimize large-scale language models, and contribute to advancements in natural language processing and computer vision.

Key Responsibilities

• Collect and prepare data for training and evaluating multimodal foundation models, including data cleaning, processing, and synthetic data creation.
• Develop and optimize large-scale language models such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs).
• Engage in tasks related to language modeling, text generation, understanding, and contextual comprehension.
• Regularly review and fine-tune Large Language Models (LLMs) to ensure optimal accuracy and relevance for custom datasets.
• Build and deploy AI applications on cloud platforms, including Azure, Google Cloud Platform (GCP), and Amazon Web Services (AWS).
• Integrate AI models with company data to enhance and augment existing applications.
• Handle data preprocessing, augmentation, and generation of synthetic data.
• Design and develop backend services using Python or .NET to support OpenAI-powered or other LLM solutions.
• Develop and maintain AI pipelines.
• Work with custom datasets, employing techniques like chunking and embeddings, for model training and fine-tuning.
• Integrate Azure Cognitive Services or equivalent platform services to enhance AI solutions.
• Collaborate with cross-functional teams for seamless deployment and integration of AI solutions.
• Ensure the robustness, efficiency, and scalability of AI systems.
• Stay abreast of the latest advancements in AI and machine learning technologies.

Skills and Experience

• Strong foundation in machine learning, deep learning, and computer science.
• Expertise in generative AI models and techniques, including GANs, VAEs, and Transformers.
• Experience with Natural Language Processing (NLP) and Computer Vision is a plus.
• Proven ability to work both independently and collaboratively within a team.
• Proficiency in advanced programming, particularly Python, and AI-centric libraries such as TensorFlow, PyTorch, and Keras.
• Knowledge of NLP for text generation projects, including text parsing, sentiment analysis, and the use of transformer models like GPT.
• Experience in data management, encompassing data preprocessing, augmentation, and synthetic data generation.
• Experience in developing and deploying AI models in production environments.
• Familiarity with cloud services (AWS, Azure, GCP) and containerization technologies like Docker and orchestration tools like Kubernetes.
• A proactive approach to bringing new ideas and innovative solutions to clients.