About the role
structured by ORIJob Details: Job Description: AI Agent Core Framework Development and Performance Optimization Design, develop, and optimize AI Agent runtimes, agent kernels, and task execution frameworks. Research planning, reasoning, tool invocation, and execution mechanisms for agents in complex task scenarios, continuously…
What you will do
- Design, develop, and optimize AI Agent runtimes, agent kernels, and task execution frameworks.
- Develop and enhance core Agent components, including workflows, memory systems, tool usage, and multi-agent collaboration.
- Build performance evaluation, profiling, and monitoring frameworks for Agent systems.
- Identify and resolve performance bottlenecks in large-scale and complex workloads, and drive the adoption of Agent technologies in areas such as software engineering productivity, intelligent operations, and automated engineering workflows.
What they are looking for
- Master’s or PhD student in Computer Science, Artificial Intelligence, Software Engineering, or a related field
- Proficient in Python with solid coding skills and good software engineering practices
- In-depth understanding of at least one area in deep learning systems or large model inference, including but not limited to: PyTorch / TorchDynamo / FX / Inductor
- LLM inference workflows (e.g., KV cache, prefill / decode stages)
- Understanding of large language models beyond API-level usage, including inference behavior, performance bottlenecks, and engineering constraints
- Strong problem decomposition skills, capable of modeling complex engineering problems into executable AI Agent task structures
Nice to have
- Experience with large model quantization techniques
- Familiarity with mainstream inference acceleration or deployment frameworks
- Knowledge of or experience in low-level kernel, operator, or performance optimization
- Hands-on experience in deploying AI Agents for real-world tasks
- Experience with complex engineering systems such as automated testing, benchmarking, CI, or performance analysis tools
- Open-source contributions related to models, systems, compilers, acceleration, or Agent frameworks
- Availability for an internship of at least 4 months, with on-site work 4 days per week or more
Full posting text
Job Details:
Job Description:
AI Agent Core Framework Development and Performance Optimization
Design, develop, and optimize AI Agent runtimes, agent kernels, and task execution frameworks. Research planning, reasoning, tool invocation, and execution mechanisms for agents in complex task scenarios, continuously improving execution efficiency, system reliability, and scalability.
Agent Core Infrastructure and Capability Development
Develop and enhance core Agent components, including workflows, memory systems, tool usage, and multi-agent collaboration. Optimize context management, task orchestration, state management, and execution pipelines to improve autonomous operation and decision-making capabilities in complex environments.
Agent Performance Analysis and Production Deployment
Build performance evaluation, profiling, and monitoring frameworks for Agent systems. Identify and resolve performance bottlenecks in large-scale and complex workloads, and drive the adoption of Agent technologies in areas such as software engineering productivity, intelligent operations, and automated engineering workflows.
Qualifications:
Basic Requirements
Master’s or PhD student in Computer Science, Artificial Intelligence, Software Engineering, or a related field
Proficient in Python with solid coding skills and good software engineering practices
In-depth understanding of at least one area in deep learning systems or large model inference , including but not limited to: PyTorch / TorchDynamo / FX / Inductor
LLM inference workflows (e.g., KV cache, prefill / decode stages)
Understanding of large language models beyond API-level usage, including inference behavior, performance bottlenecks, and engineering constraints
Strong problem decomposition skills, capable of modeling complex engineering problems into executable AI Agent task structures
Preferred Qualifications
Experience with large model quantization techniques
Familiarity with mainstream inference acceleration or deployment frameworks
Knowledge of or experience in low-level kernel, operator, or performance optimization
Hands-on experience in deploying AI Agents for real-world tasks
Experience with complex engineering systems such as automated testing, benchmarking, CI, or performance analysis tools
Open-source contributions related to models, systems, compilers, acceleration, or Agent frameworks
Availability for an internship of at least 4 months , with on-site work 4 days per week or more
Job Type:
Student / Intern
Shift:
Shift 1 (China)
Primary Location:
PRC, Shanghai
Additional Locations:
Posting Statement:
All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.
Position of Trust
N/A
Work Model for this Role
This role will require an on-site presence. * Job posting details (such as work model, location or time type) are subject to change.
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