About this role
Cognizant seeks a Gen AI Engineer to develop, fine-tune and deploy generative AI solutions. The posting specifies 5+ years of experience, lists Chennai as the job location, also states “PAN India,” and identifies a hybrid work model. It specifies a face-to-face interview mode.
Responsibilities
- Collect, clean, label, augment and prepare data—including synthetic data—for training and evaluating multimodal foundation models.
- Develop and optimize generative models, including GANs and VAEs. Work on language modeling, text generation, understanding and contextual comprehension; regularly fine-tune large language models for accuracy and relevance to custom datasets.
- Build and maintain AI pipelines. Use techniques such as chunking and embeddings with custom datasets, and develop Python or .NET backend services for OpenAI-powered or other LLM solutions.
- Build and deploy AI applications on Azure, Google Cloud or AWS. Integrate models with company data and Azure Cognitive Services or equivalent services to extend existing applications.
- Collaborate across teams on deployment and integration; support robust, efficient and scalable AI systems, stay current with AI advances, and propose innovative solutions for clients.
Qualifications and skills:
- Strong grounding in machine learning, deep learning and computer science, with expertise in generative AI techniques such as GANs, VAEs and Transformers.
- Knowledge of Python and AI libraries including TensorFlow, PyTorch and Keras; ability to implement complex algorithms. Experience managing training data and developing and deploying AI models in production.
- Knowledge of NLP techniques for text-generation projects, including text parsing, sentiment analysis and GPT models. Familiarity with AWS, Azure or Google Cloud, plus Docker and Kubernetes for deployment and scaling. Ability to work independently and with a team.
- Experience with NLP and computer vision is described as a plus.
Skills for this role
Generative AILarge Language ModelsMultimodal foundation modelsMachine LearningDeep LearningGANsVAEsTransformersGPTModel fine-tuningLanguage modelingText generationData preprocessingData augmentationSynthetic data generationData labelingChunkingEmbeddingsPython.NETTensorFlowPyTorchKerasAWSMicrosoft AzureGoogle Cloud PlatformAzure Cognitive ServicesDockerKubernetesAI pipelines