[Hiring] AI Researcher @TensorOps

Role Description

We are looking for a Master’s or PhD student to work on fine-tuning large language models (LLMs) for domain-specific tasks. The goal is to take an existing pretrained model (e.g., Meta AI’s LLaMA-class models or similar) and specialize it for a narrow, high-value use case using efficient fine-tuning techniques.

This is a hands-on applied project designed for someone who wants real-world experience deploying and optimising LLM systems.

• Help drive the next wave of applied AI by demonstrating how fine-tuned LLMs can unlock advanced, real-world use cases beyond general-purpose foundation models.
• Contribute to building specialised AI systems that deliver improved accuracy, efficiency, and control compared to out-of-the-box models.
• Bridge the gap between academic knowledge and real-world application by applying fine-tuning techniques to solve concrete business problems.

Qualifications

• 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)

Requirements

• 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 fine-tuning vs pretraining, overfitting and generalization, and model evaluation
• Strong business awareness: ability to understand the context of the fine-tuning task and translate domain requirements into clear modeling objectives

Benefits

• 100% Remote Work: Work from anywhere with flexibility and autonomy
• Dynamic, High-Impact Projects: Work on cutting-edge ML and GenAI solutions across diverse industries
• International Clients: Collaborate with global organizations and solve real-world challenges at scale
• Urban Sports Club Membership: Supporting your physical and mental wellbeing
• Monthly Bolt Credits: For rides
• Company Events & Offsites: Regular team gatherings to connect, collaborate, and celebrate