Key Responsibilities: Research and deploy LLM-based solutions (e.g., LangChain, Mastra.ai, Pydantic) for document processing, summarization, and clinical Q&A systems. Develop and optimize predictive models using scikit-learn, PyTorch, TensorFlow, and XGBoost. Design robust data pipelines using tools like Spark and Kafka for real-time and batch processing. Manage ML lifecycle with tools such as Databricks , MLflow , and cloud More ❯
impact in a senior data science role. Deep understanding of machine learning model lifecycles and optimisation. Skilled in building, training, and deploying models on large datasets. Proficiency in Python, PyTorch, Scikit-learn, and similar ML frameworks. Experience with cloud environments (AWS preferred), containerisation, and modern data infrastructure. Excellent communication skills, with the ability to work effectively across technical and non More ❯
impact in a senior data science role. Deep understanding of machine learning model lifecycles and optimisation. Skilled in building, training, and deploying models on large datasets. Proficiency in Python, PyTorch, Scikit-learn, and similar ML frameworks. Experience with cloud environments (AWS preferred), containerisation, and modern data infrastructure. Excellent communication skills, with the ability to work effectively across technical and non More ❯
