About the role
**Company:** Akoncagua AI
**Location:** Lakeland, Florida (Onsite)
**Employment Type:** Internship
We are seeking a passionate and driven AI/ML Engineer Intern to join Akoncagua.AI, where we are building next-generation domain-specific Large Language Models (LLMs) and intelligent AI solutions. In this role, you will work alongside experienced AI engineers on real-world challenges involving large-scale data processing, model training, LLM fine-tuning, evaluation, optimization, and deployment. This internship provides an opportunity to gain hands-on experience across the end-to-end machine learning lifecycle while contributing to the development of production-grade AI systems. Candidates should have a strong interest in machine learning, deep learning, transformer architectures, and Generative AI, along with solid programming, problem-solving, and data structures and algorithms skills. Experience through academic projects, research, open-source contributions, or personal work in AI/ML is highly valued.
Key Responsibilities
- Fine-tune, evaluate, and optimize Large Language Models (LLMs) for domain-specific applications.
- Work extensively with transformer architectures, including encoder-decoder and decoder-only models.
- Design and experiment with prompt engineering techniques to improve model performance and reliability.
- Prepare, clean, preprocess, and transform large-scale unstructured datasets into high-quality training datasets.
- Build and maintain scalable machine learning pipelines for training, evaluation, and deployment.
- Assist in distributed training, model optimization, quantization, and inference acceleration.
- Collaborate with AI engineers to develop and deploy production-ready ML solutions on AWS.
- Conduct research and experimentation on emerging LLM techniques, retrieval systems, and advanced deep learning architectures.
- Monitor model performance and contribute to continuous improvement initiatives.
- Participate in technical discussions, code reviews, and knowledge-sharing sessions.
Required Qualifications
- Currently pursuing a Bachelor's or Master's degree in Computer Science, Computer Engineering, Artificial Intelligence, Data Science, or a related field.
- Strong programming skills in Python.
- Hands-on experience with: PyTorch, scikit-learn, Hugging Face Transformers, Pandas
- Strong understanding of: Machine Learning fundamentals, Deep Learning, Transformer Architectures, Natural Language Processing (NLP), Large Language Models (LLMs)
- Practical experience fine-tuning transformer-based models and LLMs through academic, personal, research, or industry projects.
- Strong mathematical foundation in: Linear Algebra, Probability, Statistics, Optimization
- Experience with data preprocessing, feature engineering, data cleaning, and dataset preparation for large-scale model training.
- Familiarity with Git and software development best practices.
- Strong understanding of Data Structures, Algorithms, and Problem-Solving techniques.
Highly Preferred Qualifications
- Demonstrated expertise in transformer architectures through significant personal projects, research work, publications, or open-source contributions.
- Strong portfolio showcasing LLM fine-tuning, NLP systems, Retrieval-Augmented Generation (RAG), or deep learning projects.
- Experience with GPU-based model training and distributed training frameworks.
- Experience working with large-scale datasets using Pandas, PySpark, or distributed data processing systems.
- Previous internship, research assistantship, or industry experience in Machine Learning, NLP, Generative AI, or Deep Learning.
- Contributions to open-source AI/ML projects.
- Research publications related to Machine Learning, LLMs, NLP, or Transformer Architectures.
- Active competitive programming profile with strong performance on platforms such as LeetCode, HackerRank, Codeforces, or similar.
- Candidates who consistently solve advanced LeetCode problems and demonstrate strong algorithmic problem-solving skills will be highly preferred.