- Singapore Singapore
Shopee Hiring! Full Time AIGC Video Generation Algorithm (Leader) in - Ricebowl
Working Location
Job Description
Responsibilities
Job Description
- Technical Strategy: Define the AIGC roadmap across pre-training and post-training workstreams — from distributed training infrastructure to alignment, evaluation, and inference deployment.
- Pre-training & Infrastructure: Oversee the design of distributed training toolchains for ultra-large-scale AIGC models. Drive system-level optimization across computation, communication, and storage layers. Ensure training stability and efficiency at scale.
- Post-training & Alignment: Guide architecture design for video generation post-training — including high-quality instruction data curation, preference alignment (RLHF, DPO, GRPO, PPO), and video quality enhancement pipelines.
- Capability Expansion: Push the frontier on long-video modeling, storyline consistency, precise camera control, and multi-modal generation.
- Evaluation & Quality: Establish video quality evaluation frameworks and multi-dimensional Reward Models to systematically measure and improve output quality.
- Inference & Deployment: Drive model distillation, quantization, and inference acceleration to bring research models into production.
- Masters and above in Computer Science or any related field.
- At least 5 years of relevant experience in AI/ML, with a strong focus on generative models.
- Leadership: Demonstrated experience managing and growing a technical team with direct reports. Track record of hiring, mentoring, and retaining top talent.
- AIGC Depth: Hands-on experience in AIGC pre-training OR post-training (or both). Deep familiarity with Transformer architectures and Diffusion models (e.g., Stable Diffusion, Flux, DiT).
- Distributed Systems: Strong understanding of distributed training principles (Data/Pipeline/Tensor/Expert Parallelism) and frameworks such as PyTorch, DeepSpeed, and Megatron-LM, OR
- Post-training Expertise: Solid grasp of preference alignment methods (RLHF/DPO/GRPO/PPO), fine-tuning techniques (LoRA/QLoRA/DoRA), and distillation approaches (Consistency Models, Flow Matching).
- Communication: Excellent cross-functional communication skills. Comfortable presenting to senior leadership and collaborating across engineering, product, and research teams.
- Experience building a team or function from zero.
- End-to-end ownership of the full lifecycle of a video generation model, from data to deployment.
- Research leadership in physical simulation, world consistency, temporal consistency, or causal reasoning.
- Expertise in high-quality video evaluation and human preference alignment at scale.
- Publications at top-tier venues (NeurIPS, ICML, ICLR, CVPR, ACL, EMNLP).
- Familiarity with GPU hardware architecture, CUDA programming, NCCL, and cuDNN.
- Experience with extreme efficiency optimization such as inference acceleration, VRAM compression, quantization.
Important Information
Never provide your bank or credit card details when applying for jobs. Do not transfer any money or complete unrelated online surveys. If you see something suspicious, Report this Job ad.
Learn More