This is your opportunity to work at the cutting edge of Generative AI, data engineering, and large-scale deployment , while collaborating with world-class teams to shape the future of intelligent systems. Key Responsibilities: Develop & Enhance AI Models: Create, refine, and implement Generative AI systems and Retrieval-Augmented Generation (RAG) pipelines using frameworks like LangChain and Llama-Index. Data Engineering: Build scalable data workflows, manage ETL processes, and integrate both structured and unstructured data for AI-driven applications. Production Deployment: Deliver models into production, collaborating with DevOps to ensure performance across cloud and on-prem environments. Collaborate Across Teams: Work closely with engineers, product owners, and business leaders to ensure AI solutions drive measurable value. Innovate & Research: Stay current with emerging architectures, frameworks, and methodologies, contributing to innovation and thought leadership. Job Experience and Skills Required: Education: Degree in Computer Science, Data Science, Machine Learning, or related field. Experience: 3 years of professional experience in AI/ML, including at least 12 years in Generative AI. Practical experience with deep learning frameworks (TensorFlow, PyTorch) and generative AI libraries. Familiarity with cloud platforms (AWS, GCP, Azure) and container technologies (Docker, Kubernetes). Skills: Strong programming ability in Python and SQL, plus experience with libraries like Pandas and NumPy. Solid understanding of machine learning algorithms, neural networks, and generative models. Knowledge of large-scale data storage (Hadoop, Spark, Vector databases). Understanding of MLOps practices including model lifecycle management, monitoring, and retraining. Apply now! For more exciting Actuarial and Analytics vacancies, please visit:

This is your opportunity to work at the cutting edge of Generative AI, data engineering, and large-scale deployment , while collaborating with world-class teams to shape the future of intelligent systems. Key Responsibilities: Develop & Enhance AI Models: Create, refine, and implement Generative AI systems and Retrieval-Augmented Generation (RAG) pipelines using frameworks like LangChain and Llama-Index. Data Engineering: Build scalable data workflows, manage ETL processes, and integrate both structured and unstructured data for AI-driven applications. Production Deployment: Deliver models into production, collaborating with DevOps to ensure performance across cloud and on-prem environments. Collaborate Across Teams: Work closely with Engineers, product owners, and business leaders to ensure that AI solutions drive measurable value. Innovate & Research: Stay current with emerging architecture, frameworks, and methodologies, contributing to innovation and thought leadership. Job Experience and Skills Required: Education: Degree in Computer Science, Data Science, Machine Learning, or a related field. Experience: 3 years of professional experience in AI/ML, including at least 12 years in Generative AI. Practical experience with deep learning frameworks (TensorFlow and PyTorch) and generative AI libraries. Familiarity with cloud platforms (AWS, GCP, and Azure) and container technologies (Docker and Kubernetes). Skills: Strong programming ability in Python and SQL, plus experience with libraries like Pandas and NumPy. Solid understanding of machine learning algorithms, neural networks, and generative models. Knowledge of large-scale data storage (Hadoop, Spark, and Vector databases). Understanding of MLOps practices, including model lifecycle management, monitoring, and retraining. Apply now! For more exciting Actuarial and Analytics vacancies, please visit: