LLM Research Intern (December 2026 to April 2027)

📋 Description

• Assess domain-specific datasets and determine the right adaptation approach across fine-tuning
• Establish baseline performance and measure whether model adaptations produce meaningful, defensible
• Curate, clean, deduplicate, structure, and quality-filter datasets for training and evaluation.
• Fine-tune open-weight LLMs using techniques such as LoRA, QLoRA, PEFT, and multi-adapter approaches.
• Support training and experimentation across single-GPU and distributed multi-GPU environments.
• Design rigorous evaluation frameworks covering factuality, reasoning, grounding, robustness, domain

🎯 Requirements

• Strong programming skills in Python.
• Hands-on experience with machine learning or deep learning through research, coursework
• Solid understanding of transformer architectures, LLMs, and modern NLP concepts.
• Experience or exposure to model training and fine-tuning using tools such as PyTorch and Hugging
• Understanding of experimental design, benchmarking, model evaluation, and data quality.
• Working knowledge of model size, GPU memory, context length, training compute, inference

🎁 Benefits

• At ProCogia, you will work at the intersection of cloud, data, AI, and enterprise technology.
• You will solve real problems across commercial and regulated environments, work directly with
• You will also help shape the platform foundation supporting ProCogia’s growing AI capabilities
• This is an environment where strong engineers can build, learn, take ownership, and make a visible