· Conduct hardware-software co-design to optimize models for specific deployment targets (e.g., NVIDIA Jetson, TensorRT, FPGAs, or specialized AI accelerators).
Team Introduction: The Data-Global E-Commerce team serves as the core technological engine for ByteDance's Global E-commerce. We specialize in pioneering algorithmic and big data innovations within the E-commerce sector, driven by our mission: "To make a beautiful life readily accessible and to help unique, high-quality products reach a global market." Our work involves: Developing advanced recommendation and search algorithms to help users efficiently discover products that match their interests. Leveraging cutting-edge risk control and platform governance technologies to ensure a secure shopping environment for all users. Constructing a comprehensive product knowledge graph and intelligent customer service systems to elevate the intelligence of every stage of the transaction process. Integrating machine learning with operations research algorithms to continuously optimize supply chain and logistics efficiency, thereby reducing operational costs. Providing merchants with intelligent business tools that empower them to enhance their operational efficiency and customer service experience. By joining us, you will collaborate with world-class product and technology teams, leveraging ByteDance's extensive traffic and data ecosystem to drive the deep integration and application of technology across various e-commerce scenarios.
As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT. The Research Fellow / Research Engineer will support a research project focused on the development of data-driven modelling, optimisation, and decision-support tools for food and nutrition systems. The successful candidate will work closely with the Principal Investigator on research activities involving data analytics, computational modelling, machine learning, and optimisation. The role offers opportunities to contribute to research publications, technical development, and industry-relevant project outcomes in the areas of food sustainability, nutrition, and supply chain decision-making.
Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day.
MLOps Platform Ownership: Own the full ML platform: MLflow, Docker, AWS EKS/Kubernetes, LLM Gateway (LangFuse/PortKey), CI/CD, observability, and model monitoring. Architect the platform; delegate maintenance to team once stable.
Excellent programming abilities in leading or participating in key projects related to Search, Advertising, Recommendation systems, or Large Language Models (LLMs).
Coordinate closely with internal business units on transactions, including Accounting, Tax, SEC reporting, Finance, Investor Relations, HR, Sales/Marketing and others.
Based on Southeast Asia business scenarios and Agent applications, participate in designing AI business implementation scenarios to help improve business efficiency and solve business pain points.
Engage with technology partners, cloud providers, AI vendors and the broader technology ecosystem to explore emerging platform capabilities, evaluate new products and identify opportunities to enhance the enterprise AI platform.
Lead the implementation and operationalisation of knowledge base and retrieval-augmented generation solution stacks to support scalable GenAI and agentic use cases across business domains
PhD in Computer Science, Artificial Intelligence, Machine Learning, or related fields preferred or strong industry experience in similar fields, ideally with familiarity with Asia-Pacific/Singapore research resources.
Analyse Gen AI outputs for quality, accuracy, and alignment with requirements; identify common failure modes (hallucination, bias, irrelevant answers, factual errors).
Construct multimodal semantic links across video-product, product-product, and video-video relationships to support trend understanding, product mining, AIGC generation, and content-commerce supply optimization.