Robotics PhD Intern

Intel Corporation; Phoenix (AZ); Presencial; USD 34.000 - 55.000; A tiempo parcial

Descripción de la vacante

Intel Corporation is seeking a Systems Engineering Graduate Intern in Phoenix to help integrate hardware, software, and compute technologies into complete system solutions for robotics and Physical AI platforms.

You will gain hands-on experience with robotics hardware, AI workloads, system integration, performance optimization, and troubleshooting alongside multidisciplinary teams. This internship emphasizes hands-on lab work, simulation, and real-world testing in edge computing environments.

Formación

• This role requires pursuing a PhD in a technical field such as Computer/Electrical Engineering.
• Experience with AI/ML and robotics-related applications.
• Familiarity with Linux operating systems and development environments.
• Strong analytical and problem-solving skills.

Responsabilidades

• Support the design, integration, and validation of robotics and Physical AI platforms.
• Work with robotics hardware including sensors, cameras, compute platforms, networking equipment, and AI accelerators.
• Develop, test, and troubleshoot hardware and software solutions in a laboratory environment.
• Assist in deploying and evaluating AI and machine learning workloads on edge and robotics platforms.
• Conduct system-level debugging and root cause analysis to identify and resolve performance or integration issues.
• Measure and analyze key system metrics including latency, throughput, power consumption, and overall performance.
• Collaborate with hardware, software, silicon, and systems engineering teams to evaluate new technologies and solutions.
• Document findings, communicate technical results, and contribute to recommendations for future product development.

Educación

PhD in Computer Engineering

Herramientas

ROS/ROS 2

Descripción del empleo

Job Details

Job Description:

As a Systems Engineering Graduate Intern, you will help develop and validate next-generation Robotics and Physical AI platforms by integrating hardware, software, and Intel compute technologies into complete system solutions. Working alongside multidisciplinary engineering teams, you will gain hands‑on experience with robotics hardware, AI workloads, system integration, performance optimization, and technical troubleshooting.

This role is ideal for candidates passionate about robotics, artificial intelligence, and system‑level engineering who want to contribute to cutting‑edge technologies while developing practical industry experience.

What You Will Do

• Support the design, integration, and validation of robotics and Physical AI platforms.
• Work with robotics hardware including sensors, cameras, compute platforms, networking equipment, and AI accelerators.
• Develop, test, and troubleshoot hardware and software solutions in a laboratory environment.
• Assist in deploying and evaluating AI and machine learning workloads on edge and robotics platforms.
• Conduct system‑level debugging and root cause analysis to identify and resolve performance or integration issues.
• Measure and analyze key system metrics including latency, throughput, power consumption, and overall performance.
• Collaborate with hardware, software, silicon, and systems engineering teams to evaluate new technologies and solutions.
• Document findings, communicate technical results, and contribute to recommendations for future product development.

Qualifications

Minimum Qualifications

• Currently pursuing a PhD degree in Computer Engineering, Electrical Engineering, or a related technical field
• Knowledge of computer architecture and computing systems, including CPUs, GPUs, and AI accelerators.
• Experience through coursework, research, academic projects, or internships in AI/ML and robotics-related applications.
• Familiarity with Linux operating systems and development environments.

Preferred Qualifications

• Strong academic performance with a cumulative GPA of 3.0 or higher preferred.
• Experience with ROS/ROS 2 or other robotics software frameworks.
• Hands‑on experience debugging and troubleshooting hardware and software systems.
• Understanding of AI model deployment and system performance evaluation.
• Experience working with robotics hardware, sensors, cameras, and embedded systems.
• Familiarity with AI inference, edge computing, and real‑time applications.
• Experience benchmarking and optimizing AI or robotics workloads.
• Understanding of networking concepts and system integration.
• Prior laboratory or research experience in Robotics, Autonomous Systems, or Physical AI.
• Strong analytical and problem‑solving skills.