Skill Set:

- Generative AI, LLM, RAG, Model Fine-tuning, Deep-Learning, Transformers (Please interview internally and Upload only pre-vetted pro

Experience:

- Proven experience in developing and working with state-of-the-art large language models (LLMs) such as GPT, BERT, T5, or other transformer-based models.
- Strong expertise in training, fine-tuning, and optimizing LLMs for real-world applications.
- Hands-on experience with ML frameworks like TensorFlow, PyTorch, Hugging Face Transformers, etc.
- Experience with advanced techniques in NLP such as attention mechanisms, transfer learning, and few-shot learning.
- Practical knowledge of deploying AI models at scale in production environments.

Skills:

- Expertise in deep learning and machine learning algorithms, particularly in the context of generative models.
- Proficiency in programming languages like Python, and familiarity with libraries such as NumPy, Pandas, Scikit-learn, and others.
- Familiarity with cloud-based solutions and tools (AWS, GCP, or Azure) for scalable model training and deployment.
- Knowledge of distributed computing and parallelism for large-scale training.

- As a Generative AI Engineer specialized in Large Language Models (LLMs), you will work on developing, implementing, and optimizing state-of-the-art generative models that tackle a wide range of complex challenges in AI.



You will be part of a multidisciplinary team pushing the frontiers of language understanding and generation, contributing to the research, development, and deployment of large-scale AI systems that can generate coherent, contextually aware, and human-like text.

Key Responsibilities:

- Research Development: Lead and contribute to research initiatives focused on generative models, particularly LLMs like GPT, BERT, T5, and cutting-edge transformer architectures.
- Model Design Implementation: Design, implement, and optimize LLM architectures for text generation, completion, summarization, and other NLP tasks.
- Training Fine-Tuning: Conduct training and fine-tuning of large-scale models on specialized datasets, leveraging up-to-date machine learning frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers.
- Optimization: Work on scaling, optimizing, and improving the efficiency of large models, including distributed training, parallelism, and hardware acceleration (GPUs, TPUs).
- Deployment Integration: Collaborate with engineering teams to integrate generative models into production systems and applications, ensuring the scalability, robustness, and efficiency of deployed models.

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 MBSE AI/ML Professional (Chennai)
🏢 Satven
📍 Chennai