LLM Architect - AI/ML in Delhi, भारत

Role Summary : Design and develop production-ready AI/ML solutions using LLMs, Generative AI, NLP, deep learning, and cloud AI services. Act as a technical SME, collaborate across teams, and drive scalable AI solutions from design through https://jobeax.com/link/XIA7wD9gSNU9qtiD Responsibilities : - Design, develop, and deploy scalable, production-ready AI/ML and GenAI solutions.- Build and integrate LLM-based applications, NLP solutions, and cloud AI services.- Collaborate with cross-functional teams to define solutions and drive key technical decisions.- Troubleshoot complex AI/ML challenges and provide effective solutions across teams.- Provide technical guidance, mentoring, and knowledge sharing to team members.- Monitor solution performance, quality, and project progress to ensure successful delivery.Must-Have Qualifications : - 8+ years of overall professional experience, with substantial hands-on AI/ML engineering experience.- Strong hands-on experience with Large Language Models (LLMs) and GenAI.- Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.- Experience with NLP and cloud platforms such as AWS, Azure, or GCP.- Experience building scalable, production-ready AI solutions.- Strong technical leadership and problem-solving https://jobeax.com/link/l9VxKPoHxfPAR8Dc to Have : - Experience with RAG, embeddings, and vector databases.- Knowledge of LLM fine-tuning, AI agents, or LLMOps/MLOps.- Experience with Docker, Kubernetes, and CI/CD.- Exposure to multimodal AI, computer vision, or image https://jobeax.com/link/JEurfFNiCbGhGzq9 Competencies : - Strong problem-solving and analytical skills.- Effective communication and collaboration.- Technical leadership and decision-making.- Ownership and accountability.- Mentoring and knowledge https://jobeax.com/link/TzMt1HvdrHyrmjKz Join Us : - Work on enterprise-scale AI and Generative AI initiatives.- Solve complex business problems using emerging LLM and cloud AI technologies.- Work alongside multidisciplinary engineering and technology teams.- Influence AI solution architecture and production engineering practices.- Build expertise across LLMs, GenAI, cloud, NLP, deep learning, and AI engineering.- Contribute to a culture of continuous learning, innovation, collaboration, and knowledge sharing. (ref:hirist.tech)