AI Engineer - Intern

About the role

About Intel

Intel develops semiconductor technologies and computing solutions that support a broad range of applications and industries. This internship provides hands-on experience working on AI software solutions, applied research, and hardware-software integration in a collaborative engineering environment.

About the Role

Intel is seeking an AI Software Engineering PhD Intern to contribute to the design, development, and optimization of AI software solutions.

The role spans areas such as computer vision, machine learning, deep learning, AI algorithms, frameworks, and AI software architecture. You will have the opportunity to implement and tune AI models, conduct applied research, work on data and feature engineering, and contribute to hardware-software integration.

As an intern, you will apply academic knowledge to practical projects supporting Intel's business goals while developing technical skills and exploring future career opportunities.

Key Responsibilities

Contribute to the design, development, and optimization of AI software solutions.

Work with AI algorithms, frameworks, and software architectures.

Develop solutions across areas including:

Computer Vision

Machine Learning

Deep Learning

Image Processing

Assist in implementing and tuning AI models for performance and accuracy.

Contribute to applied AI research projects.

Work on hardware-software integration for AI solutions.

Support the development of AI software solutions in collaboration with internal product teams and external partners.

Contribute to system-level deployment of AI applications.

Help develop scalable and efficient AI solutions.

Perform data engineering and preparation activities.

Apply feature engineering techniques to support AI and machine learning workflows.

Analyze data imbalance and noisy datasets.

Contribute to AI projects involving explainability tools.

Work collaboratively with engineering and research teams.

Required Qualifications

Current PhD candidate enrolled in an accredited Engineering or Computer Science program.

Academic emphasis in Artificial Intelligence, particularly in areas such as:

Federated Learning

Image Classification

Multiscale Attention for Object Detection

Computer Vision

Image Processing

Feature Engineering

Minimum 3.0 GPA with a demonstrated record of academic success.

Research or coursework experience with explainability tools.

Knowledge of data engineering and preparation.

Experience with feature engineering.

Understanding of data imbalance and noisy datasets.

Strong foundation in:

Linear Algebra

Statistics

Probability

Strong analytical and problem-solving skills.

Effective communication and teamwork abilities.

Self-motivated approach to research and engineering work.

Experience or skills with:

Python

C++

PyTorch

TensorFlow

OpenCV

Familiarity with:

Git

Cloud technologies and concepts

Containers

Docker

MLOps

Preferred Qualifications

Experience deploying AI applications in production environments where high levels of precision and accuracy are required.

Experience working in the semiconductor industry or a similar technical environment.

First-author research publications in leading computer vision or AI conferences such as:

CVPR

ICCV

NeurIPS

Portfolio of projects in Computer Vision / Image AI.

Open-source contributions, research projects, or relevant technical publications.

AI & Machine Learning Focus

The internship provides exposure to a broad range of AI engineering and research areas, including:

Artificial Intelligence

Machine Learning

Deep Learning

Computer Vision

Image Classification

Object Detection

Image Processing

Federated Learning

Feature Engineering

Multiscale Attention

Explainable AI

AI Model Optimization

AI Software Architecture

Applied AI Research

Data Engineering & Model Development

You will contribute to preparing and processing data for AI applications, including:

Data Engineering

Data Preparation

Feature Engineering

Data Imbalance Analysis

Noisy Dataset Handling

Model Performance Optimization

Model Accuracy Optimization

These activities support the development and tuning of AI models for practical applications.

Software & MLOps Technologies

Programming & AI Frameworks

Python

C++

PyTorch

TensorFlow

OpenCV

Development & Infrastructure

Git

Docker

Containers

Cloud Technologies

MLOps

Hardware-Software Integration

The role may involve integrating AI software with hardware systems and contributing to system-level deployment.

This includes supporting scalable and efficient AI solutions and collaborating with product teams and external partners to translate AI research and engineering work into practical systems.

Research & Innovation

Candidates with strong academic research experience will have the opportunity to contribute to applied AI research.

Relevant research areas include computer vision, image AI, federated learning, image classification, object detection, feature engineering, explainability, and AI model optimization.

A portfolio of research papers, open-source contributions, or computer vision projects is particularly relevant to the position.

Work Arrangement

This is an onsite internship.

Primary Location: Phoenix, Arizona

Additional Location: Hillsboro, Oregon

Shift: Shift 1 — United States of America

Job posting details, including work model and location, may be subject to change.

Compensation & Benefits

The listed annual salary range is:

$170,598 – $170,602 USD

Intel notes that internship rates are based on factors including degree, location, and job role, and the recruiter can provide more information regarding the specific compensation applicable to the candidate's preferred location and role.

The compensation package may include:

Competitive pay

Stock bonuses

Health benefits

Retirement benefits

Vacation benefits

Ideal Candidate Profile

The ideal candidate is a PhD researcher and AI engineer with strong academic experience in artificial intelligence, computer vision, or related areas and hands-on skills in modern AI development frameworks.

You should be comfortable combining mathematical foundations with practical software engineering, data preparation, model development, experimentation, and deployment. Research experience, technical publications, and a portfolio of computer vision or Image AI projects are valuable for this role.

Position of Trust

Position of Trust: N/A

Responsible Hiring

Intel states that it does not charge recruitment, medical examination, or other fees as a condition of employment. Candidates should report any request for such fees to their recruiter.

Equal Opportunity

Intel provides employment consideration to qualified applicants without regard to characteristics protected by applicable law, regulation, or ordinance.

Application Focus

Candidates should highlight relevant experience in AI research, computer vision, deep learning, Python, C++, PyTorch, TensorFlow, OpenCV, feature engineering, explainability, MLOps, Docker, cloud technologies, and AI model deployment.