Design, build, and productionize agentic systems (multi-step reasoning, tool orchestration, guardrails) for materials science search, Q&A and information extraction.
Design, develop, integrate and optimise scalable AI/ML solutions, including LLM-based applications, Retrieval-Augmented Generation (RAG), agentic AI and multimodal AI solutions to address Home Team use cases.
Design, build, and maintain end-to-end machine learning pipelines on Databricks, covering data preparation, feature engineering, model training, evaluation, and deployment.
Analyze large-scale datasets to solve complex business and technical challenges in gaming through analytics, forecasting, machine learning, recommender systems, generative AI, experimentation, causal inference, and econometrics.
Support the deployment, configuration, and maintenance of high-end servers, storage servers, networking equipment, and software components in secure environments.
Performance Profiling & Optimization: Utilize profiling tools (e.g., Nsight, PyTorch Profiler) to identify bottlenecks in data loading, gradient computation, and communication. Implement optimizations like kernel fusion, sharding, and tiling to improve step time.
Work with POSH business functions to understand operational workflows, identify AI opportunities, and validate that proposed solutions address the right problems.
Conduct skills gaps analysis and training needs assessment, to develop training roadmaps and tailor training to address the gaps. Organize and/or conduct programmes to equip MPA officers with the knowledge and skills to perform his job productively.
Design, build, and productionize agentic systems (multi-step reasoning, tool orchestration, guardrails) for materials science search, Q&A and information extraction.