Responsibilities

• Lead innovation initiatives and exploration of GenAI technologies
• Stay abreast of the latest developments in generative AI research and contribute to Proof-of-Concept projects
• Democratisation of GenAI
• Drive and promote the democratisation of GenAI across the organization
• Develop and promote standards to ensure consistency and quality in GenAI implementations

• Support in building and nurturing a GenAI Center of Excellence (CoE)
• Identify capabilities and provide guidance, mentor, training, and problem-solving assistance
• Enable business units and functions in leveraging GenAI capabilities effectively
• AI Design and Development, and Maintenance:
• Design AI solutions for business use cases, encompassing both existing and new systems and processes
• Design and implementation of generative AI and machine learning models
• Running AI and ML Ops for IT-managed applications
• Support in managing vendors to achieve defined delivery and operations objectives

• Optimise generative models & prompts for performance, scalability, and efficiency
• Experiment with advanced generative algorithms such as GANs, VAEs, MoE (Mixture of Experts), Large-language Model (LLM) Merging and others

• Analyse and pre-process large datasets to uncover patterns relevant to Generative AI Modelling
• Handling different modalities of data including unstructured text, image, audio and video
• Analyse the model response and track the LLM model drift and data drift for optimal retraining of GenAI models 
• Contribute to data quality and feature engineering processes to enhance model performance

• Deploy generative models into production environments
• Collaborate with software engineer for seamless integration into applications and systems

• Stay updated with the latest advancements in AI, GenAI and machine learning
• Contribute to projects to push the boundaries of GenAI technologies

Requirements

• Bachelor’s degree in IT, Computer Science, AI / ML Engineering, Business Analytics or equivalent
• Minimum of 10 years of professional experience in the data engineering and analytics field, including 5 years in Data Science / AI / Machine Learning engineering with a focus on Generative AI technologies
• Proficiency in programming languages such as Python,Rust and SQL
• Expertise in Generative AI frameworks and libraries, e.g., LangChain, LlamaIndex, AutoGen, CrewAI, Langraph, llamacpp & OpenAI. 
• Expertise in Data science and machine learning frameworks and libraries, such as Scikit-learn, TensorFlow, and PyTorch.
• Strong understanding of data pre-processing, feature engineering, and model evaluation techniques. 
• Good knowledge on Prompt engineering techniques and cost optimization strategies for Closed Source LLMs.
• Experience in fine-tuning open-source Large Language Models (LLMs) such as Llama 2, Gemma, Mixtral, Phi-2, Orca2,function calling LLMs etc. 
• Proficiency in developing LLM-based RAG (Retrieval Augmented Generation)
• Familiarity with cloud-based AI services and platforms, with a preference for Azure.
• Good knowledge of Multimodal language models, embeddings, including Llava, GPT-4V, and Gemini. 
• Experience working with closed-source Large Language Models, e.g., OpenAI, Gemini & mistral.
• Good understanding of embedding models and embedding pipelines.
• Supports specific types of AI applications pipelines with Vector databases & Graph databases. 
• Ability to develop LLMbased agentic workflows to support suitable business use cases. 
• Experience with Git and Agile software project management tools, such as JIRA, Confluence, and CI/CD pipelines. 
• Strong experience in converting business requirement into technical requirement and providing end to end solution flow for AI applications