AI / ML Engineer

Support development and validation of machine learning and statistical models for business use cases

· Assist in building forecasting and predictive models using established techniques and libraries

· Contribute to Generative AI use cases including prompt development, evaluation, and basic experimentation with LLMs

· Support Retrieval-Augmented Generation (RAG) workflows including document ingestion, embeddings, and retrieval

· Perform data preparation, feature engineering, and exploratory data analysis

· Work with structured and unstructured data from enterprise sources and AI platforms

· Collaborate with software engineers to integrate models into applications and pipelines

· Help document models, assumptions, results, and data pipelines

· Monitor model performance and assist with troubleshooting and improvements

· Participate in agile ceremonies including sprint planning, stand-ups, and retrospectives

· Build scalable AI/ML models for given use cases, including price elasticity and recommendation systems, ensuring applicability/reusability across multiple business units.

· Leverage tools such as Databricks and AWS SageMaker to manage data, build models, and deploy solutions.

· Collaborate with stakeholders, understanding their needs and translating them into AI/ML solutions.

· Continually monitor and evaluate the effectiveness of AI/ML models and forecasting techniques, making necessary adjustments to optimize performance.

· Stay abreast of the latest AI/ML trends and technologies, identifying opportunities for innovation and improvement.