Overview The AI Engineer is responsible for designing, developing, and deploying intelligent systems that leverage machine learning (ML), deep learning (DL), and data science techniques. This role bridges the gap between data science and software engineering, ensuring that AI models are not only accurate and efficient but also scalable and production ready. The AI Engineer collaborates across teams to transform data into actionable insights and intelligent automation solutions. Responsibilities Design and Implement ML Models and AI AlgorithmsDevelop custom models tailored to business problems. Select appropriate algorithms based on data characteristics and project goals. Prototype and iterate on model architectures using frameworks. Preprocess and Analyse Large DatasetsClean, transform, and normalize raw data for model readiness. Perform exploratory data analysis (EDA) to uncover patterns and insights. Engineer features that enhance model performance. Train, Evaluate, and Optimize ModelsSplit data into training, validation, and test sets. Train models using appropriate hyperparameters and optimization techniques. Evaluate model performance using metrics like accuracy, precision, recall. Tune models to improve generalization and reduce overfitting. Deploy AI Models into Production EnvironmentsPackage models into APIs or microservices using tools like Flask, FastAPI, or Docker. Integrate models into existing software systems or cloud platforms (e.g., AWS, Azure, GCP). Monitor model performance post-deployment and implement retraining pipelines if needed. Collaborate with Data Scientists and Software EngineersWork closely with data scientists to understand modelling goals and data nuances. Partner with software engineers to ensure seamless integration of AI components. Participate in code reviews, design discussions, and agile ceremonies. Qualifications Bachelor’s Degree in Data Science, Computer Science, Mathematics, Statistics, Information Technology, Information Systems or a related field – (essential). Experience +1 years’ experience in a Data Scientist or similar role with good exposure to the application of machine learning, deep learning, data mining and mathematical and/or statistical methodology to support business objectives – (essential). Experience in a retail, commercial or IT environment – (desired). Knowledge and Skills Basic knowledge of SQL, Python and data science toolkits – (essential). Proficiency in MS Office 365 with well-developed Excel skills – (essential). Exposure to delivering project outcomes using design thinking, lean and agile principles – (desired). #J-18808-Ljbffr