Centered on the deployment needs of Tencent's overseas gaming business in large language model (LLM) and reinforcement learning scenarios, this role is responsible for the development, performance optimization, and engineering implementation of high-quality AI computing infrastructure. Specific responsibilities include:
1. Distributed Training Engineering: Participate in the implementation of large-scale distributed training solutions; own the engineering delivery of data parallelism, model parallelism (Tensor Parallelism / Pipeline Parallelism), and ZeRO techniques; continuously tune GPU utilization and ensure the stability of ultra-large-scale training jobs.
2. Compute Scheduling Optimization: Take a deep role in developing and optimizing AI job scheduling logic; Address compute bottlenecks in complex gaming scenarios through fine-grained resource management, fault self-healing mechanisms, and efficient checkpointing strategies.
3. End-to-End Model Engineering: Own the full engineering pipeline from model training to inference serving; participate in operator profiling, model quantization, and the construction of high-performance inference pipelines to support rapid AI iteration within gaming products.
4. AI-Driven Engineering Evolution: Actively embrace AI Coding tools to boost development efficiency; drive Harness Engineering practices — including automated testing and engineering governance — to ensure extreme reliability of the underlying infrastructure.
1. Bachelor's degree or above; majors in Computer Science, Computer Architecture, High-Performance Computing, or related fields preferred.
2. Core Tech Stack: Proficient in at least one of Python / C++ / Go; deep understanding of the PyTorch framework; hands-on experience engineering distributed training with DeepSpeed, Megatron-LM, or equivalent frameworks.
3. Solid understanding of distributed systems principles; Familiarity with NCCL, RDMA networking, or high-performance storage is a plus; working knowledge of containerized infrastructure (Docker / Kubernetes).
4. Demonstrable experience with AI Coding tools (e.g., GitHub Copilot, Cursor) is a strong plus; prior work in Harness Engineering — engineering governance, automated benchmarking, or system stress testing — is highly valued.
5. Exceptional learning agility, clear logical thinking, and the ability to collaborate effectively with cross-functional teams on complex systems engineering challenges; Fluent proficiency in English
6. Bonus: Background in high-performance backend architecture, or real project experience in LLM training / inference engineering.
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.
Skills Required
- Bachelor's degree or above
- Proficient in at least one of Python / C++ / Go
- Deep understanding of the PyTorch framework
- Hands-on experience engineering distributed training with DeepSpeed or Megatron-LM
- Solid understanding of distributed systems principles
- Familiarity with NCCL, RDMA networking, or high-performance storage is a plus
- Working knowledge of containerized infrastructure (Docker / Kubernetes)
- Experience with AI Coding tools (e.g., GitHub Copilot) is a strong plus
- Prior work in Harness Engineering is highly valued
- Fluent proficiency in English
- Background in high-performance backend architecture is a bonus
Tencent Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Tencent and has not been reviewed or approved by Tencent.
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Healthcare Strength — Healthcare coverage is positioned as a standout, with strong PPO options and relatively low prescription costs highlighted for U.S. plans. This suggests the medical offering can be a meaningful component of the overall rewards package for U.S.-based employees.
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Retirement Support — Retirement support is framed as competitive in the U.S., with employer match details called out as an item to confirm in writing. This indicates retirement benefits can be a notable strength where applicable.
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Strong & Reliable Incentives — Performance-linked incentives and share-based awards are repeatedly included as part of the compensation model, alongside potential RSU and sign-on eligibility in certain roles. This points to total rewards often extending beyond base pay through variable and equity components.
Tencent Insights
What We Do
Tencent uses technology to enrich the lives of Internet users. Our communications and social platforms Weixin and QQ connect users with each other, with digital content and daily life services in just a few clicks. Our high performance advertising platform helps brands and marketers reach out to hundreds of millions of consumers in China. Our financial technology and business services support our partners' business growth and assist their digital upgrade. We invest heavily in talent and technological innovation, actively participating in the development of the Internet industry. Tencent was founded in Shenzhen, China, in 1998, and listed on the Main Board of the Stock Exchange of Hong Kong since June 2004.
