Gen AI Engineer

Cognizant; Gandhinagar, Ahmedabad District; Ibrido; INR 3.000.000 - 5.500.000; Tempo pieno

Descrizione del lavoro

Cognizant is seeking a Gen AI Engineer to work on data preparation, model development, and deployment of AI solutions. You will build and optimize large-scale language models, work with multimodal data, and deploy AI applications on cloud platforms such as Azure, AWS, or GCP. Strong skills in Python and ML frameworks are required.

The role involves collaborating with cross-functional teams, implementing AI pipelines, and staying abreast of AI advancements to deliver robust, scalable solutions.

Competenze

• Strong foundation in ML/DL and CS concepts.
• Experience with generative AI models and techniques (GANs/VAEs/Transformers).
• NLPer with NLP and CV knowledge is a plus.

Mansioni

• Handle data preprocessing, augmentation, and synthetic data generation.
• Design and develop backend services using Python or .NET to support OpenAI-powered solutions.
• Develop and maintain AI pipelines and workflows.
• Train and fine-tune models with custom datasets (chunking/embeddings).
• Integrate Azure Cognitive Services or equivalent cloud services to extend AI capabilities.
• Collaborate with cross-functional teams for deployment and integration.
• Ensure robustness, efficiency, and scalability of AI systems.
• Stay updated on latest AI/ML advances.

Conoscenze

Generative AI

NLP

Python

TensorFlow

PyTorch

Keras

GPT models

Cloud platforms

Azure

AWS

GCP

Docker

Kubernetes

Data preprocessing

AI pipelines

Descrizione del lavoro

Role: Gen AI Engineer

Experience : 5+ to 13 Years

Location : Gift City (Gandhi Nagar Gujarat)

Notice Period : Immediate to 60 days

Mode of Interview : In-Person drive

Interview Date: 17th Oct 2026 (Saturday)

Note: Scheduled In-Person Drive only

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