Build and optimize end-to-end machine learning pipelines, handling large-scale datasets, noisy labels, model training, evaluation and deployment, while improving model accuracy, robustness and inference efficiency.
Apply data preprocessing techniques to optimize large sets of sensor data processing and analysis, handling issues like noise, missing data, and time-series synchronization.
Work with clients and senior teammates to analyze business challenges, map workflows (service blueprints) to better understand customer journey in order to identify gaps and opportunities for AI/ML use cases.
Lead the design and development of chatbot and automation workflows using Microsoft technologies such as MS OpenAI, AI Search, AI Foundry, and Power Platform, while conducting evaluations of large language models from key market providers.
Collaborate with cross-functional stakeholders including engineering, manufacturing, automation, IT, and operations teams to deliver end-to-end digital solutions.
Collaborate with cross-functional stakeholders including engineering, manufacturing, automation, IT, and operations teams to deliver end-to-end digital solutions.
Data & Pipeline Support: Connect data sources to Microsoft Fabric and support reliable data pipelines and warehouse structures. Use SQL to prepare data for dashboards and AI solutions, ensuring accuracy, consistency, and quality.
Act as the voice of the legal customer: Provide structured feedback to Product Marketing, Product, and Engineering on customer needs, usability, and adoption barriers. Help refine product capabilities and contribute to playbooks, best practices, and scalable customer-engagement assets.
Validate workflows and outputs, improve accuracy, reliability and efficiency based on user feedback, and maintain practical workflow documentation and user guides.
・Work with clients from the early stage: understand their business, define requirements, and translate the "what" into the "how" (architecture, technology choices, scope, and estimates).