(Senior) 3D Model Generation AI Researcher

Tencent
London
1 year ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer - Research

Environmental Data Scientist/Hydrologist

Data Analyst - FTC

Senior Data Engineer - Energy

Responsibilities:

LightSpeed Studios is one of the world’s most innovative and successful game developers. With team across China, United States, Singapore, Canada, United Kingdom, France, Japan, South Korea, New Zealand, and United Arab Emirates. We are expanding to more countries.

Founded in 2008, LightSpeed Studios has created over 50 games across multiple platforms and genres for over 4 billion registered users. It is the co-developer of worldwide hits
PUBG MOBILE, Apex Legends Mobile, and League of Legends: Wild Rift (Chinese Version).

Responsibilities:

- Responsible for developing AI systems to generate high-quality 3D models from textual descriptions or image inputs, suitable for game production and other applications.

- Optimize AIGC large models (3D generation) to improve generation quality, speed, diversity, and controllability, and promote industrial deployment and product implementation of 3D generation models.

- Collaborate across teams to seamlessly integrate 3D models into game environments, enhance player experience, and promote the application of AI technology in specific business scenarios.

Requirements:

Requirements:

- in computer vision or computer graphics, with 3 or more years of relevant work experience.

- Outstanding achievements in areas such as 3D mesh model generation, mesh texturing and PBR material generation, automatic skeleton binding, and mesh automatic skinning.

- Experience in using and training AI models such as Diffusion, ViT, DiT, GAN, ControlNet, LoRA, IP-Adapter, Inpainting, super-resolution, etc.

- Experience in constructing 3D datasets (characters, objects, scenes) and various 3D data processing (Mesh, Voxel, NeRF, Triplane, SDF, GaussianSplatting, FlexiCubes, etc.).

- Publications in top computer vision and graphics conferences and journals (such as CVPR, ICCV, ECCV, SIGGRAPH/Asia, NIPS, ICML, PAMI, IJCV, TOG, TVCG, etc.).

- Strong ability to learn, self-drive, clear logical thinking, excellent communication skills, and teamwork abilities.

- Practical experience with 3D modeling software (, Maya, Blender, 3DS Max) or game engines (, Unity, Unreal Engine) is preferred.

- Proficiency in at least one programming language (such as Python, C/C++), mastery of deep learning frameworks, strong coding skills, with preference for ACM regional contest gold medalists or contributors to influential open-source projects.

#LI-RL1

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.