About The Role

We are looking for a Software Intern to help us adapt open-weight large language models to security and identity work. You will take a model from raw data to a measured result: preparing datasets, running fine-tuning jobs, and building the evaluations that tell us whether a change helped.

This is a Fall/Winter internship: hands-on work with real models and real GPUs, alongside the founding team. If you have already fine-tuned a model and want to do it on problems that matter, this is the role for you.

Responsibilities

What you’ll own.

Data & training

- Collect, clean, and prepare training and evaluation datasets.
- Fine-tune open-weight LLMs with SFT and parameter-productive methods (LoRA / QLoRA).
- Run and monitor training jobs on GPUs, and make the most of limited compute.

Evaluation
- Build evaluation sets and benchmarks that reflect the tasks we care about.
- Compare models and training runs, and report clearly what worked and what did not.

Required Skills What you’ll bring day one.

Core

- PyTorch and the Hugging Face ecosystem (Transformers, Datasets, PEFT).
- Hands-on experience with open-weight LLMs.
- Fine-tuning: SFT, LoRA / QLoRA.
- Dataset preparation for training and evaluation.
- Model evaluation.
- GPU fundamentals: memory, batch sizes, mixed precision.

Nice to Have
- Domain-adaptive or continued pretraining (DAPT).
- Synthetic data generation.
- CUDA.
- Docker.
- vLLM for serving and fast inference.
- Experiment tracking (Weights & Biases, MLflow or similar).
- Evaluation frameworks and harnesses.
- Reinforcement learning for LLMs.

Why Join Us 01

Train and evaluate real models, not a sandbox project.

02

Work directly with the founding team.

03

Learn how AI meets security and cryptographic identity.

📌 Software Intern (Toronto)
🏢 Arkion-tech
📍 Toronto