Senior Researcher, Multi-Modality

Placeholder Company for Greater China

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Singapore-CapitaSky Until 9/16/2026 H-1B sponsor history First posted July 18, 2026 Last posted July 18, 2026
Job description

Business Unit

LIGHTSPEED STUDIOS is made up of passionate players who advance the art & science of game development through great stories, great gameplay, and advanced technology. We are focused on bringing next generation experiences to gamers who want to enjoy them anywhere, anytime, across multiple genres and devices.

About the Hiring Team

Lightspeed Tech Center is a R&D department under Lightspeed Studios which develop PUBG Mobile and other high-quality games. Our Tech Center leads the research, exploration, and discovery of innovative technologies and provides technical services for all games during all phases of life cycle, including engine, audio, QA, AI, next generation game, technical cooperation, etc.

What the Role Entails

We're looking for a Senior Researcher in multi-modality to help shape the next generation of multimodal foundation models and agentic AI within gaming scenarios. This role focuses on AI research and applications for in-game contexts — abstracting research problems from real game business scenarios, solving them, and deploying solutions that serve a wide range of gaming use cases. You'll work on multimodal understanding, post-training, and agent research, driving breakthroughs that advance both the scientific frontier and Tencent's game products at scale.
  • Pioneer new research directions in multimodal understanding, post-training, reasoning, grounding, and agent planning, grounded in real gaming scenarios.
  • Abstract research problems from game business scenarios, solve them, and land solutions that serve diverse in-game applications.
  • Advance the understanding capabilities of multimodal large models (VLMs/MLLMs) across images, video, text, and audio.
  • Lead post-training methodologies — SFT, RLHF/RLAIF, reward modeling, and preference alignment — to improve model capability and reliability.
  • Design and execute experiments end-to-end: from data and benchmarking, to training, evaluation, and iteration.
  • Collaborate with engineers to bring research prototypes into production and deploy them across game scenarios at scale.
  • Publish at top-tier conferences and contribute to the broader research community.
     

Who We Look For

  • PhD in Computer Science, ML, or a related field, or equivalent research experience.
  • Expertise in one or more of: multimodal understanding and vision-language reasoning; pre-/post-training of LLMs/VLMs; reinforcement learning and LLM-based agents; representation learning.
  • Ability to abstract research problems from real business (ideally gaming) scenarios and drive them to deployment.
  • Consistent first-author publications at leading venues (NeurIPS, ICML, CVPR, ACL, etc.).
  • Strong implementation skills in modern ML frameworks (PyTorch, JAX, etc.).
  • Proven ability to run complex experiments, analyze results, and iterate quickly.
  • Passion for high-impact research with real-world applications.
     

Equal Employment Opportunity at Tencent

As an equal opportunity employer, we firmly believe that diverse voices fuel our innovation and allow us to better serve our users and the community. We foster an environment where every employee of Tencent feels supported and inspired to achieve individual and common goals.

About this role

Summary

Research and develop multimodal AI models for gaming applications.

Job title

Senior Researcher, Multi-Modality

Experience level

PhD or equivalent research experience

Industry

software

Location requirements

Singapore, remote work not specified

Salary

Not specified

Visa sponsorship

H-1B sponsor history

Management role

No

Skills & keywords

Required skills

PhD in CS or related fieldmultimodal understandingvision-language reasoningpre/post-training of LLMs/VLMsreinforcement learningPyTorchJAX

Preferred skills

publications at top conferencesmodel deploymentexperiment analysis

Specializations

multimodal understandingAIlarge modelspost-trainingagent research
Locations

Structured locations inferred from the posting.

Unknown location

Work arrangement unknown
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