TensorOps - AI Researcher

• Strong Python skills • Experience with deep learning frameworks: PyTorch (preferred) or TensorFlow • Experience with Hugging Face Transformers or similar ecosystems • Hands-on experience training or fine-tuning transformer models on GPUs (local or cloud-based) • Previous experience using cloud platforms for model training or deployment (e.g., AWS, GCP, Azure, RunPod or similar GPU providers) • Experience working with or fine-tuning open-weight LLM families (Gemma-3, Qwen-3.5, Llama 4, GPT-OSS, Mistral...) • Hands-on experience with LoRA • Understanding of: • Understanding of: • Fine-tuning vs pretraining • Overfitting and generalization • Model evaluation • Strong business awareness: ability to understand the context of the fine-tuning task and translate domain requirements into clear modeling objectives • MSc or PhD student in Computer Science, Machine Learning, AI, or related field • Alternatively, 6 months of hands-on experience training and fine-tuning deep learning models • Has worked on LLMs in research or industry • Has fine-tuned at least one transformer model • Comfortable working independently • Interested in applied AI and real-world constraints (cost, latency, memory) • What You’ll Gain • What You’ll Gain • Real-world experience fine-tuning large models (30B–100B parameter class) • Exposure to production constraints and deployment • Opportunity to co-author technical writeups if applicable • Strong applied portfolio project