Qureos

FIND_THE_RIGHTJOB.

AI Engineer Intern

JOB_REQUIREMENTS

Hires in

Not specified

Employment Type

Not specified

Company Location

Not specified

Salary

Not specified

Requirements and responsibilities


Overview

We are seeking a motivated and talented AI Engineer Intern to join our engineering and research team. This role offers an opportunity to work on real-world artificial intelligence and machine learning projects, contributing to innovative solutions that drive automation, optimization, and intelligence across our products and systems.

Responsibilities

Assist in designing, developing, and implementing AI and machine learning models.

Work on data preprocessing, feature engineering, and exploratory data analysis.

Collaborate with data scientists, ML engineers, and software developers to deploy and optimize models.

Evaluate model performance and fine-tune algorithms for improved accuracy and efficiency.

Contribute to the development of tools, APIs, or pipelines that support AI applications.

Research and prototype new algorithms or AI-driven techniques to solve domain-specific problems.

Document findings, code, and experimental results clearly for team-wide knowledge sharing.

Qualifications

Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.

Strong programming skills in Python (knowledge of TensorFlow, PyTorch, or scikit-learn is a plus).

Solid understanding of machine learning concepts, neural networks, and data structures.

Experience with data analysis and libraries such as NumPy, pandas, and Matplotlib.

Familiarity with cloud computing (AWS, GCP, or Azure) or MLOps is a plus.

Excellent problem-solving skills and attention to detail.

Strong communication and teamwork abilities.

Preferred Skills

Experience with LLMs (Large Language Models), NLP, or computer vision projects.

Knowledge of API integration and model deployment frameworks (e.g., FastAPI, Flask).

Understanding of version control systems such as Git/GitHub.

Exposure to data pipelines, ETL processes, or data engineering tools.

© 2025 Qureos. All rights reserved.