Build and maintain an automated LLM evaluation pipeline covering multiple dimensions, including general capabilities, Agent capabilities, and persona/role-playing. The pipeline should support one-click evaluation, historical result comparison, and regression testing.
Conduct reinforcement learning (RL) training experiments for long-horizon tasks, including hyperparameter tuning, performance analysis, and iterative optimization.
Build and maintain an automated LLM evaluation pipeline covering multiple dimensions, including general capabilities, Agent capabilities, and persona/role-playing. The pipeline should support one-click evaluation, historical result comparison, and regression testing.
Conduct reinforcement learning (RL) training experiments for long-horizon tasks, including hyperparameter tuning, performance analysis, and iterative optimization.
Work closely with other research team members to research, develop, and integrate AI and XR technologies for railway operations, inspection, maintenance, and training.
Research and develop existing computer vision algorithms and incorporate novel techniques or create new algorithms from ground up to solve desired use cases
Build AI-Powered Engineering Platforms: Design and develop internal developer platforms, including AI gateways, agent orchestration frameworks, retrieval systems, and reusable engineering services that enable product teams to safely and effectively leverage AI.
Explore and implement advanced AI concepts such as agentic AI, Model Context Protocol (MCP) servers, Retrieval-Augmented Generation (RAG), prompt engineering, and -query decomposition to enhance model performance
Drive strategic planning, governance, and stakeholder management by developing and implementing a roadmap for AI and GenAI initiatives, establishing governance frameworks and policies, monitoring compliance, and engaging with business leaders, IT teams, and other stakeholders to promote the benefits of AI technologies.
As a Data Acquisition Engineer (AI Systems), you will work at the intersection of software engineering, browser automation, distributed systems, and AI. You will help design and build platforms that collect, process, and deliver structured data from a wide range of public sources while continuously improving their reliability and resilience.
Oversee the various line of efforts with the multifaceted teams, including the research, product management, data science, to curate and chart AI strategies for the respective Centres of Excellence (COEs)
Strategic Advisory: Partner with CxOs and senior technology leaders to define AI transformation roadmaps, enterprise AI strategy, and operating models for responsible and sustainable AI adoption.
Architectural Leadership: Own the technical vision, end-to-end design, and deployment of our high-performance, full-stack, on-premises AI infrastructure.