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Alibaba Intelligent Engine · AI Infra

Join ROCK and the Intelligent Engine AI Infra Team

The Intelligent Engine department belongs to Alibaba Holding Group's Platform Technology organization. It builds internal search, recommendation, advertising, and AI engineering systems. The rapid growth of AIGC brings new challenges: improving large-model training and inference performance and cost, reshaping model development workflows, and addressing new demands from online model services.

We provide a complete engineering system for group users, spanning data, training, evaluation, prediction, application development, and solutions. Working closely with the Happy family model teams, we co-develop multimodal generative large models and take on core responsibilities for Alibaba Group multimodal generation model development.

We value a strong technical culture and open sharing. The team has contributed open-source projects including ROLL, Megatron-LLaMA, XDL, and Euler, and continues to share outcomes with the broader community.

Who We Are

Focus Areas

The Search & Governance Platform builds foundational engineering platforms for Alibaba Group LLMs and multimodal models. The team provides large-scale agent training environments for LLMs and high-performance inference services for the HappyHorse and HappyOyster model families.

Large-scale Agent Training Environments

Build ROCK, a large-scale agent training environment framework for post-training, evaluation, and data production, covering reinforcement learning environment development, deployment, and management.

Large Model Engineering Platform

Build foundational engineering platforms for Alibaba Group LLMs and multimodal models, supporting training, evaluation, prediction, and application development for the HappyHorse and HappyOyster model families.

Multimodal Understanding and Generation Inference

Optimize the full stack for VL, Omni, DiT, Diffusion Model, and AR architectures, from low-level kernels to inference service scheduling, balancing model quality, performance, and cost.

HappyHorse Inference Engineering

Deliver production inference for leading multimodal understanding and generation models in AI applications, spanning inference architecture, end-to-end service orchestration, and performance optimization.

Selected Results

Selected Results

As the Alibaba HappyHorse inference engineering team, we bring leading multimodal understanding and generation models into AI applications, covering inference architecture design, end-to-end service orchestration, and deep performance optimization.

Open Source

Open Source Frameworks and Systems

Megatron-LLaMA

An open-source LLM training framework based on Megatron, supporting efficient distributed training.

LLMPyTorch
GitHub

X-DeepLearning (XDL)

Alibaba's open-source sparse model training framework for large-scale recommendation and advertising.

SparseRecSys
GitHub

ROLL

An open-source RL training framework for efficient distributed RL post-training at scale.

RLDistributed
GitHub

ROCK

An open-source reinforcement learning environment development framework that simplifies environment development, deployment, and management.

RL EnvAgent
GitHub

Euler

Alibaba's open-source distributed graph learning engine for large-scale GNN training.

GNNGraph
GitHub

RecIS

A large model training framework for recommendation and advertising at industrial scale.

RecSysTraining
GitHub

Open Roles

Open Roles

Select a role or apply button to open the Alibaba Talent page.

Application

How to Join

  1. Choose a role above and submit your application through Alibaba Talent.
  2. You can also send your resume to lxm02049624@alibaba-inc.com and contact HR on WeChat: 19952378952.
  3. Ask an Alibaba colleague who shared the role to refer you internally.