AIML and Generative AI Engineer

Cognizant; Ernakulam, Dadri, Coimbatore District; Hybrid; INR 1,500,000 - 3,000,000; Full time

Job summary

Cognizant is seeking a Data Science and Gen AI Engineer to lead data preparation, model development, and deployment across Pan India. You will build multimodal foundation models, integrate AI with cloud platforms, and collaborate with cross-functional teams to deliver scalable AI solutions.

The role requires 5–14 years of experience, strong ML/DL fundamentals, and hands-on work with GANs/VAEs, NLP, and computer vision.

Qualifications

• Experience with multimodal foundation models data prep and synthetic data generation.
• Develop and optimize large-scale language models (GANs, VAEs, transformers).
• NLP and computer vision familiarity a plus.
• Proficient in Python and AI libraries (TensorFlow, PyTorch, Keras).
• Experience deploying AI models in production and on cloud platforms.

Responsibilities

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

Skills

ML/DL fundamentals

Generative AI (GANs/VAEs/Transformers)

Python & AI libraries

NLP & CV basics

Cloud platforms (AWS/Azure/GCP)

Docker & Kubernetes

OpenAI/LLM integrations

Tools

Docker

Kubernetes

Cloud services tooling

Job description

Role: Data Science and Gen AI Engineer

Location: Pan India

Experience: 5 to 14 Years

Notice Period: Immediate to 90 days

Mode of Interview: Scheduled In-Person Drive only (Kochi, Noida, Coimbatore)

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