Machine Learning Resident - Client: Pratt & Whitney Canada (6 month term)
Confidential“If you are interested in applying machine learning (ML) to real-world industrial challenges in aerospace – particularly optimizing decisions for parts allocation and maintenance operations through data analytics and explainable ML - this is a perfect opportunity for you. Be a part of a team of research and machine learning scientists and get mentored by some of the best minds in AI while doing it. ” Xu Han, Machine Learning Scientist About the Role This is a paid Residency that will be undertaken over a 6-month period. The Resident will be reporting to an Amii Scientist and regularly consult with the Pratt & Whitney Canada team to share insights and engage in knowledge transfer activities. Also, please note that the top candidate(s) will be subject to a security check, and the results of which will be shared with Pratt & Whitney Canada. About our Client Pratt & Whitney Canada (P&WC) is a global leader in the aerospace industry, headquartered in Longueuil, Quebec. We manufacture next-generation engines that power the world’s largest fleet of business, general aviation, and regional aircraft and helicopters. For nearly 100 years, we have pioneered advancements in engine development, supporting cargo and equipment, transportation, wildfire suppression, and passenger travel. About the Project While the project has a lot of different branches, the strongest focus will be on developing a tool to schedule different activities in the production flow. The solution must be custom-tailored to the needs of different departments and needs to be able to optimize based on multiple different factors. It is crucial that the tool is properly documented to account for potential changes in priorities and focus. Analytics of historical data will be the foundation of the optimization. Who You Are You have completed a graduate-level program or higher (M.Sc./Ph.D.) in Computing Science, AI/ML, Engineering, or a related field, with substantial research or project experience in ML and optimization—particularly in forecasting, predictive modeling, time series analysis. You possess strong Machine Learning Engineering (MLE) skills to drive end-to-end development and deployment of AI solutions. You have a deep understanding of metrics and evaluation practices, along with the capacity to contextualize scientific metrics for business applications. You are proficient in Python and familiar with key ML frameworks and libraries such as Scikit-learn, TensorFlow, PyTorch, and Pandas. Your positive attitude toward learning new applied domains, especially in aerospace or manufacturing, and your ability to communicate technical concepts clearly make you a valuable team player who is enthusiastic about collaborating across interdisciplinary teams. What You Will Be Doing In this role, you will be instrumental in developing, refining, and operationalizing high-quality, end-to-end AI products for Pratt & Whitney Canada. Your work will focus on creating predictive and prescriptive models for various AI modules (such as cost optimization, work scheduling, parts allocation, procurement, and inventory management) using real-world data. You will explore and implement a range of ML and optimization techniques, including supervised and unsupervised learning, forecasting, and classification models. You will be responsible for data preprocessing, including handling missing data, noise reduction, and synchronization issues. You will also productionize AI solutions on existing enterprise data infrastructure using MLOps tools. Furthermore, you will help establish a strong AI governance framework compliant with P&WC security and AI best practices, support the P&WC AI team in refining and industrializing initial models, and participate in the experimentation and piloting of developed solutions. You will collaborate with interdisciplinary teams, participate in project meetings, and contribute to reports on model performance and project milestones. Your e…