Posted:2 months ago| Platform: Linkedin logo

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Job Description

Generative AI Model Development: Design, train, and fine-tune LLMs (GPT, LLaMA, Claude), diffusion models, and multimodal AI systems for various applications. NLP & Deep Learning Expertise: Implement and optimize Transformer-based architectures (BERT, T5, GPT, etc.) for text generation, summarization, and embeddings. AI Pipeline Engineering: Develop end-to-end AI pipelines , including data preprocessing, model training, inference, and deployment using PyTorch, TensorFlow, or JAX. Agile Development: Work in an Agile/Scrum environment, participating in standups, sprint planning, and retrospectives to iteratively develop AI-driven products. Fine-tuning & Optimization: Optimize pre-trained models through LoRA, PEFT, quantization, and distillation for efficiency and cost-effectiveness. Cloud & MLOps Integration: Deploy AI models on AWS using Kubernetes, Docker, FastAPI, and serverless architectures . Vector Databases & Retrieval-Augmented Generation (RAG): Work with FAISS, ChromaDB, Weaviate, or Pinecone to enhance generative models with retrieval-augmented techniques. AI Security & Ethics: Implement safeguards against bias, hallucinations, adversarial attacks , and ensure compliance with AI governance frameworks (e.g., GDPR, HIPAA). Experimentation & Research: Stay up-to-date with the latest AI advancements, conduct A/B testing , and experiment with new zero-shot, few-shot, and fine-tuning techniques. Collaboration & Mentorship: Work with cross-functional teams (data scientists, software engineers, product teams) and mentor junior AI engineers. Show more Show less

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Tata Consultancy Services

Information Technology and Consulting

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