Machine Learning Engineer

Senior Machine Learning Engineer - LLM, NLPs. My client is a leader in the biotechnology and data science sector, focused on leveraging advanced computational tools to drive innovations in healthcare, genomics, and personalised medicine. They are seeking a highly skilled Bioinformatician with extensive experience in Large Language Models (LLMs) and Natural Language Processing (NLP) to join their cutting-edge team. The successful candidate will play a pivotal role in enhancing their computational capabilities by integrating state-of-the-art machine learning techniques, particularly LLMs and NLP, into their bioinformatics workflows. This position will contribute directly to the development of advanced tools and methodologies designed to decode complex biological data, aligning with the companys mission to advance precision medicine. Key Responsibilities: Apply sophisticated machine learning methods, including deep learning, optimisation, and causal analysis, to develop innovative models for biological data analysis. Build and refine tools, libraries, and frameworks to streamline and enhance the company’s machine learning product pipelines. Lead efforts to optimise current AI processes, focusing on improving the efficiency, accuracy, and scalability of bioinformatics applications. Design and improve retrieval-augmented generation (RAG) systems tailored for biological data processing. Effectively translate complex technical findings into actionable insights for the product team, ensuring alignment with business goals. Participate in the full software development lifecycle, from design and development to deployment, testing, and iterative improvement. Required Qualifications: PhD in Bioinformatics, Biology or Genetics. Over 5 years of experience in developing and deploying machine learning models, particularly in systems for personalised data analysis. Demonstrated experience in implementing machine learning models at scale within production environments. Proficiency in Python, with strong skills in relevant data science and machine learning libraries such as TensorFlow, PyTorch, scikit-learn, and pandas. Familiarity with leading LLM frameworks (e.g., Langchain, Llamaindex, HuggingFace) and evaluation tools like Ragas or Presidio. For more information on the position, please APPLY or reach out to me directly.