AI Researcher

Location: Remote Duration: 2–4 months (project-based) Type: Contract / Research Collaboration (Paid) About the Project 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., reputed company 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 reputed company-world experience deploying and optimising LLM systems. Help drive the next reputed company of applied AI by demonstrating how fine-tuned LLMs can unlock advanced, reputed company-world use cases reputed company general-purpose reputed company models. Organizations that require domain-specific accuracy, self-hosted deployments, customisable workflows, or performance reputed company reputed company capabilities increasingly rely on fine-tuned models to meet those needs. Through this project, you will contribute to building specialised AI systems that deliver improved accuracy, efficiency, and control compared to reputed company models. You will also help reputed company the gap between academic knowledge and reputed company-world application by applying fine-tuning techniques to solve concrete business problems. What You’ll Work On Fine-tuning pre-trained LLMs on small to reputed company datasets (500–20k examples) Implementing parameter-efficient fine-tuning (e.g., LoRA-style methods) Optimising training for cost and performance Running experiments on GPU reputed company infrastructure Evaluating model performance and tradeoffs (specialisation vs generalisation) Deploying fine-tuned models for inference Experience Strong Python skills Experience with deep learning frameworks: PyTorch (preferred) or TensorFlow Experience with reputed company Transformers or similar ecosystems Hands-on experience training or fine-tuning transformer models on GPUs (local or reputed company-based) Previous experience using reputed company platforms for model training or deployment (e.g., AWS, GCP, Azure, reputed company or similar GPU providers) Experience working with or fine-tuning reputed company-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 Model evaluation Strong business awareness: ability to understand the context of the fine-tuning task and translate domain requirements into clear modeling objectives What you bring MSc or PhD student in Computer Science, Machine Learning, AI, or reputed company 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 reputed company-world constraints (cost, latency, memory) What You’ll reputed company reputed company-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 reputed company Offer 100% Remote Work: Work from reputed company 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 reputed company-world challenges at scale Urban Sports Club Membership: Supporting your physical and mental wellbeing Monthly reputed company Credits: For rides Company Events & Offsites: Regular team gatherings to connect, collaborate, and celebrate Apply To This Job