TWG Global aims to drive innovation and business transformation across its diverse portfolio by leveraging data and AI as core assets, enabling informed decision-making, and ensuring responsible data and AI practices.
Requirements
- architect and deploy groundbreaking machine learning (ML) and AI solutions
- scalable ML models and cloud-based AI platforms
- high-performance data pipelines that enable lightning-fast training and inference
- agentic AI systems, orchestrating multi-agent workflows that leverage sub-agents for tasks like semantic search, data retrieval, and automated analysis, all integrated with ontology-driven knowledge bases
- latest ML and generative AI advancements - like large language models (LLMs), recommendation engines, and agentic platforms
- craft personalized AI experiences, evolve reference architectures for cloud-native AI/ML
- cloud engineering, ML optimization, and collaborative innovation
Responsibilities
- Assist in developing and deploying machine learning (ML) models to improve applicant generation and ranking for multimodal feed recommendations (e.g., image, text), and participate in applied ML research to enhance model performance.
- Collaborate with research, engineering, and product teams to help integrate new ML innovations into feed products and services, contributing to improved user experiences.
- Support the implementation of advanced personalization features and exploration capabilities, helping to drive improvements in product metrics and user engagement.
- Contributes to the design and development of scalable frontend and backend solutions, following best practices in technical design, test automation, and code quality.
- Help optimize ML models and data pipelines to ensure robust and efficient operations for first-party products and services.
- Work with cross-functional teams—including program managers, data engineers, data scientists, and business analysts—to support the integration and execution of AI/ML solutions and assist in resolving system issues.
- Participate in cloud engineering projects to help enable scalable ML platforms for training and deploying cloud-based AI/ML solutions, focusing on performance and security.
Other
- collaborate with management to advance our data and analytics transformation
- empowering informed decision-making for both customers and employees
- prioritize responsible data and AI practices, ensuring ethical standards and regulatory compliance
- strategic partnerships with leading data and AI vendors fuel transformative projects
- empowering leaders and teams to slash costs, spark new revenue, and dominate markets - all while upholding top-tier quality, security, and compliance
