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Skills
Analysis Skillsunmatched
Artificial Intelligence (AI)unmatched
Artificial Intelligence (AI) Agentsunmatched
Cloud Computingunmatched
Communication Skillsunmatched
Computer Engineeringunmatched
Computer Scienceunmatched
Emerging Technologyunmatched
GPU (Graphics Processing Unit)unmatched
High Availabilityunmatched
Inference Engineunmatched
Kernel Programmingunmatched
Memory Hardwareunmatched
Onboardingunmatched
Open Sourceunmatched
Performance Managementunmatched
Public Cloudunmatched
Software Engineeringunmatched
Team Playerunmatched
Description
About the team
Compute division focuses on building large-scale and highly available cloud infrastructure, which supports both public cloud products (like VolcEngine ECS service) and the internal products. The Compute-US team focuses on the development and research of the compute infrastructure platform.
We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.
Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume.
Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.
Responsibilities
Develop key technologies to optimize our AI Infra stack, including training infra, inference infra, and AI agents.
Work with academia and open source communities on joint development.
Follow the latest technologies from academia or industry and conduct deep-dive analysis.
Present our research and products in academic papers.Minimum Qualifications:
Individuals who are completing or have recently completed a Master's degree in Computer Science, Computer Engineering, or a related discipline.
Experience with at least one of the following areas:
LLM training infra, including optimizations for various post-training workloads such as RL training, knowledge distillation, etc.
LLM inference infra, including inference engine performance improvements, more efficient execution parallelism, GPU kernel optimizations, etc.
AI Agent Infra, including computer-use agents, coding agents, agent memory, agent sandbox, etc.
Commit to proactive continuous learning, demonstrate enthusiasm for AI technologies, and exhibit a strong ability to quickly grasp and apply new technologies.
Good communication and teamwork skills.
Preferred Qualifications:
Frequent contributors or maintainers in AI Infra related open source communities such as vLLM or SGLang.
Having CS conference publications such as OSDI or MLSys.