AI/ML Engineer

Position summary

Responsibilities

• Support development and validation of machine learning and statistical models for business use cases.
• Build forecasting and predictive models using established techniques and libraries.
• Contribute to Generative AI use cases through prompt development, evaluation, and basic LLM experimentation.
• Support RAG workflows involving document ingestion, embeddings, and retrieval.
• Perform data preparation, feature engineering, and exploratory data analysis on structured and unstructured data.
• Collaborate with software engineers to integrate models into applications and pipelines.
• 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 reusable AI/ML models for price elasticity and recommendation use cases.
• Use Databricks and AWS SageMaker to manage data, build models, and deploy solutions.
• Collaborate with stakeholders to translate business needs into AI/ML solutions.