AI/ML Engineer Intern

Overview

We are seeking a high-potential AI/ML Engineer Intern to join our team and work on real-world, production-grade AI systems. This internship is designed for top-tier Computer Science students or recent graduates who are passionate about large language models (LLMs), deep learning, and building scalable machine learning systems.

You will work alongside experienced engineers on cutting-edge AI initiatives, gaining hands-on experience across the full ML lifecycle—from data preparation and model training to evaluation and deployment. This is a high-impact, learning-intensive role with the opportunity to contribute meaningfully to production systems.

This internship is structured as a pipeline to full-time employment. High-performing interns will be considered for full-time AI/ML engineering roles upon completion.

Key Responsibilities

- Collaborate with AI/ML engineers to develop, fine-tune, and evaluate machine learning and LLM-based models

- Assist in designing and testing prompt engineering strategies to improve model performance and output quality

- Build and maintain ML pipelines for training, evaluation, and deployment workflows

- Preprocess, clean, and transform structured and unstructured data into high-quality, model-ready datasets

- Contribute to model optimization efforts for improved inference efficiency and scalability

- Work on NLP, computer vision, or related ML tasks under mentorship

- Run experiments, benchmark models, and analyze performance results

- Research and explore new techniques, architectures, and tools in LLMs and deep learning

Required Qualifications

- Currently pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field

- Strong programming skills in Python

- Solid understanding of machine learning fundamentals and deep learning concepts

- Familiarity with ML frameworks such as PyTorch, TensorFlow, or scikit-learn

- Basic understanding of transformer architectures and modern NLP techniques

- Strong foundation in mathematics (linear algebra, probability, and statistics)

- Demonstrated interest in AI/ML through coursework, projects, or internships (e.g., GitHub portfolio)

Nice to Have

- Experience working with LLMs, prompt engineering, or fine-tuning techniques

- Prior internship, research experience, or meaningful academic projects in AI/ML

- Experience with data preprocessing tools such as Pandas or PySpark

- Exposure to cloud platforms (AWS, GCP, or Azure) or GPU-based training environments

- Experience with Git and collaborative software development workflows

- Contributions to open-source projects or strong competitive programming profiles (e.g., LeetCode, HackerRank)

Compensation & Benefits

- Competitive hourly stipend: $15–$25/hour (based on experience and skill level)

- Opportunity to work on real-world AI systems and impactful projects

- Direct mentorship from experienced AI/ML engineers

- Exposure to modern AI tools, frameworks, and infrastructure

- Potential for full-time employment upon successful completion of the internship

What You’ll Gain

- Hands-on experience building and deploying production-grade AI/ML systems

- Exposure to LLMs, prompt engineering, and modern deep learning workflows

- Experience working in a fast-paced, collaborative engineering environment

- A strong foundation for transitioning into a full-time AI/ML engineering role

Why Join Us

- Work on cutting-edge AI technologies with real-world impact

- Learn from experienced engineers and accelerate your growth

- Contribute to meaningful AI projects beyond academic work

- Join a team focused on building scalable, production-ready AI systems