Software Engineer — Distributed LLM Inference Systems

Intel Corporation; Prescott (AZ); On-site; USD 52,000 - 82,000; Full time

Job summary

Intel Corporation in Shanghai is hiring a College Grad Software Engineer to contribute to distributed LLM inference systems within the AI Frameworks team. You will design, implement, and optimize components for high-performance AI software on diverse hardware, collaborating with researchers and engineers to push AI capabilities forward.

The role emphasizes distributed algorithms, model/data parallelism, and efficient communication, with a strong foundation in Python and C++ and knowledge of

Qualifications

• Master’s degree or higher in Computer Science, AI, or related field.
• Proficiency in Python and modern C++ programming.
• Foundational knowledge of deep learning frameworks (e.g., PyTorch).
• Experience debugging and optimizing software for performance.
• Strong problem-solving and quick learning of unfamiliar systems.

Responsibilities

• Design, develop, and optimize distributed LLM inference systems and AI framework components.
• Implement distributed algorithms and asynchronous communication for deep learning.
• Develop components like schedulers, workers, and KV cache management.
• Profile workloads to identify bottlenecks in compute, communication, memory, and scheduling.
• Collaborate with teams to improve latency, throughput, and scalability.

Skills

Python

C++

PyTorch

Distributed systems

Performance optimization

Education

Master’s degree in CS/AI/Software Engineering

Tools

Git

Job description

Job Details:

Job Description:

The Role and Impact：

• As a Software Engineer on Intel’s Artificial Intelligence Frameworks team, you will contribute to designing, developing, and optimizing distributed inference systems for large language models.
• Your day-to-day work will involve implementing distributed inference algorithms, optimizing model execution and communication, transforming neural network models, and developing software components that improve inference performance across diverse hardware architectures. You may work on areas such as disaggregated serving, request scheduling, KV cache management, parallel execution, and efficient communication between inference components.
• By collaborating with researchers and engineers, you will play a key role in advancing Intel's AI capabilities and ensuring industry-leading solutions.

Business Group： Intel's Artificial Intelligence Frameworks team is dedicated to empowering transformative AI solutions by developing and optimizing software frameworks for machine learning and deep learning. This group works on enhancing the performance of AI applications across diverse computing hardware backends while contributing to open-source communities. As part of Intel, this team supports the mission to drive technological innovation and deliver impactful AI advancements globally.

Key Responsibilities

• Design, develop, and optimize distributed LLM inference systems and related AI framework components.
• Implement distributed algorithms, including model/data parallel frameworks and asynchronous communication for deep learning.
• Develop and optimize components such as request schedulers, model workers, communication layers, and KV cache management mechanisms.
• Profile distributed inference workloads to identify computation, communication, memory, and scheduling bottlenecks.
• Collaborate with component teams to improve end-to-end latency, throughput, scalability, and resource utilization.
• Contribute high-quality code, tests, and documentation to internal and open-source projects while following industry engineering standards.

Qualifications:

Minimum Qualifications –

• Master’s degree in computer science, Artificial Intelligence, Software Engineering, or a related field, with 0-1 years of hands‑on experience demonstrated through internships, academic projects, coursework, or training.
• Proficiency in Python and modern C++ programming.
• Foundational knowledge of deep learning and AI frameworks, such as PyTorch.
• Experience debugging and optimizing software for performance.
• Basic understanding of machine learning algorithms and techniques.
• Strong problem-solving skills and the ability to learn unfamiliar systems quickly.

Preferred Qualifications

• Experience or project exposure related to distributed LLM inference and serving.
• Experience in contributing to open-source projects or collaborating within open-source ecosystems.
• Understanding of LLM inference concepts such as prefill and decode, KV cache management, continuous batching, parallelism strategies, and disaggregated serving.
• Familiarity with inference engines or serving frameworks such as vLLM, SGLang, TensorRT-LLM, or similar technologies.
• Knowledge of large language models and inference optimization techniques.
• Knowledge of AI Agent architecture and execution workflows, including tool calling, planning, memory, context management, and multi-agent coordination.
• Effective communication skills, including fluency in written and spoken English.

Take the opportunity to be part of Intel's journey in redefining AI frameworks and enabling groundbreaking innovations. Your contributions will shape the future of AI software and its real-world impact.

Job Type:

College Grad

Shift:

Shift 1 (China)

Primary Location:

PRC, Shanghai

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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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.