CHN - Minhang, China · hace 2 semanas
Como becario de ingeniería de software de IA, diseñarás, desarrollarás y optimizarás runtimes de agentes de IA, componentes centrales y marcos de evaluación de rendimiento, incluido el trabajo en la eficiencia de inferencia de LLM y el despliegue en producción.
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. * ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter. Intel’s official careers website. Find your next job and take on projects that shape tomorrow’s technology. Benefits Internships Life at Intel Locations Recruitment Process
Publicada el 19 oct 2026
