Key Responsibilities

• Lead the entire ML lifecycle from data collection and analysis to model deployment, monitoring, and optimization.
• Apply deep learning and NLP techniques to develop solutions, potentially enhancing systems like search or recommendation engines.
• Design and implement end-to-end ML pipelines, incorporating MLOps best practices for CI/CD, containerization (Docker, Kubernetes), and cloud deployment (AWS, GCP, Azure).
• Utilize LLM knowledge, including prompt engineering and fine-tuning, to build advanced generative AI applications and conversational AI solutions.
• Perform comprehensive data analytics, including statistical anal...