Senior AI Engineer

Role: Senior AI Engineer Position : Remote we are looking 14+ years of experience In IT Role Overview: A highly skilled Generative AI / Large Language Model Specialist with expertise in domain-specific dataset preparation, advanced fine-tuning, and multi-step agentic system design. The ideal candidate will have hands-on experience working with medical data, along with a strong background in reinforcement learning, reward modelling, and embedding optimization. Key Responsibilities: 1. Domain-Specific Dataset Preparation – Curate, preprocess, and structure medical chart datasets, including comprehensive patient records (medical history, diagnoses, treatments, test results) while adhering to compliance and privacy requirements. 1. Tokenization for Specialized Data – Apply and optimize tokenization strategies tailored to domain-specific language, ensuring high model efficiency and accuracy. 1. Advanced LLM Fine-Tuning – Perform parameter-efficient and full fine-tuning of LLMs, incorporating reinforcement learning with human feedback (RLHF) and reward modelling techniques. 1. Model Evaluation & Benchmarking – Define and implement fine-tuned evaluation metrics, benchmark models, and analyse system performance to ensure reliability and accuracy. 1. Agentic Architecture Design – Architect and implement multi-step, reasoning-capable AI agents, leveraging embedding tuning for optimal task execution. Qualifications: • Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or related field • Proven track record in medical NLP or domain-specific LLM projects. • Strong understanding of transformer architectures, embedding models, and prompt engineering. • Proficiency in Python and ML frameworks (e.g., PyTorch, Cuda). • Familiarity with RLHF, reward modelling, and evaluation frameworks. Nice to Have: • Prior work in multi-agent AI systems. • Experience with embedding Optimization vector databases and knowledge graphs. • Contributions to open-source LLM projects.