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-effective 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