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Cognizant Linkedin · Posted 1mo ago

Gen AI Engineer

India

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Indexed description

Role –Gen AI Engineer

Location: AIA-Bangalore

Exp: 3 to 12 years

Job Description

  • Collect and prepare data for training and evaluating multimodal foundation models. This may involve cleaning and processing text data or creating synthetic data.
  • Develop and optimize large-scale language models like GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders)
  • Work on tasks involving language modeling, text generation, understanding, and contextual comprehension.
  • Regularly review and fine-tune Large Language models to ensure maximum accuracy and relevance for custom datasets.
  • Build and deploy AI applications on cloud platforms – any hyperscaler Azure, GCP or AWS.
  • Integrate AI models with our company's data to enhance and augment existing applications.

Role & Responsibility

  • Handle data preprocessing, augmentation, and generation of synthetic data.
  • Design and develop backend services using Python or .NET to support OpenAI-powered solutions (or any other LLM solution)
  • Develop and Maintaining AI Pipelines
  • Work with custom datasets, utilizing techniques like chunking and embeddings, to train and fine-tune models.
  • Integrate Azure cognitive services (or equivalent platform services) to extend functionality and improve AI solutions
  • Collaborate with cross-functional teams to ensure smooth deployment and integration of AI solutions.
  • Ensure the robustness, efficiency, and scalability of AI systems.
  • Stay updated with the latest advancements in AI and machine learning technologies.

Skills & Experience

  • Strong foundation in machine learning, deep learning, and computer science.
  • Expertise in generative AI models and techniques (e.g., GANs, VAEs, Transformers).
  • Experience with natural language processing (NLP) and computer vision is a plus.
  • Ability to work independently and as part of a team.
  • Knowledge of advanced programming like Python, and especially AI-centric libraries like TensorFlow, PyTorch, and Keras. This includes the ability to implement and manipulate complex algorithms fundamental to developing generative AI models.
  • Knowledge of Natural language processing (NLP) for text generation projects like text parsing, sentiment analysis, and the use of transformers like GPT (generative pre-trained transformer) models.
  • Experience in Data management, including data pre-processing, augmentation, and generation of synthetic data. This involves cleaning, labeling, and augmenting data to train and improve AI models.
  • Experience in developing and deploying AI models in production environments.
  • Knowledge of cloud services (AWS, Azure, GCP) and understanding of containerization technologies like Docker and orchestration tools like Kubernetes for deploying , managing and scaling AI solutions
  • Should be able to bring new ideas and innovative solutions to our clients
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