AI Solution Architect - Graduate Intern

• Assist in deploying and validating AI accelerator systems and multi-node AI clusters.
• Support cluster bring-up activities, including system provisioning, software installation, and health verification.
• Execute performance benchmarks and collect system telemetry.
• Help troubleshoot system, networking, and software issues in AI environments.

System Debugging and Validation:

• Analyze hardware, firmware, driver, and software logs to identify failures.
• Assist with validation of BIOS, firmware, and system software configurations.
• Support development of test plans and automated validation workflows.
• Participate in root-cause investigations of system performance and stability issues.
• AI/ML Workloads
• Deploy and evaluate AI models using frameworks such as PyTorch and vLLM.
• Benchmark AI workloads and identify performance bottlenecks.
• Assist in reproducing customer-reported issues in lab environments.
• Contribute to optimization studies for AI inference and training workloads.

Automation and Tool Development:

• Develop Python-based tools to automate testing, monitoring, and data collection.
• Create dashboards, scripts, and utilities for cluster management and diagnostics.
• Contribute to documentation, runbooks, and technical knowledge bases.
• End-to-End AI Solutions
• Participate in building end-to-end AI solutions, such as generative AI, agentic AI, computer vision, robotics, or intelligent automation projects.
• Work with cross-functional teams to integrate hardware, software, AI models, and applications into complete solutions.

• Currently pursuing Master's in: Computer Science, Computer Engineering, Electrical Engineering, Data Science, or AI/ML or related fields
• Experience with Python programming.
• Familiarity with Linux command line and system administration concepts.
• Understanding of computer architecture, operating systems, networking, or distributed systems.
• Demonstrated ability to solve complex engineering or technical problems through coursework, research, personal projects, robotics competitions, hackathons, open-source contributions, or previous internships.
• Strong analytical and problem-solving skills.
• Ability to work independently and collaborate in a team environment.

• Python, C/C++, or Bash scripting
• Linux/Unix environments
• Git and software development workflows
• Docker or containerized applications

• PyTorch, TensorFlow, or other AI frameworks
• LLMs, RAG, agentic AI, or generative AI applications
• Cloud or cluster computing environments
• GPU or AI accelerator technologies

Project Experience - Coursework, research, personal projects, or internships involving:

• AI/ML applications
• Robotics systems
• Autonomous systems
• Computer vision
• Distributed computing
• High-performance computing (HPC)
• End-to-end AI solution development

Soft Skills:

• Strong communication and presentation skills.
• Curiosity and willingness to learn new technologies.
• Ability to diagnose problems systematically and communicate findings clearly.

• AI accelerator and cluster architecture
• AI infrastructure deployment and operations
• System-level debugging and performance optimization
• AI model deployment and benchmarking
• Automation, monitoring, and validation frameworks
• Customer-facing AI solution development and deployment best practices

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.