Job Description

"If you are interested in applying machine learning to real-world industrial challenges in aerospace - particularly building predictive models from sensor data, extracting insights from technical documents and user feedback - 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."


Subhojeet Pramanik, Machine Learning Scientist


About the Role



This is a paid Residency that will be undertaken over a 12-month period with the potential to be hired by Pratt & Whitney Canada afterwards (note: at the discretion of the client). 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



In the dynamic and highly competitive aerospace industry, the adoption of advanced technologies such as Artificial Intelligence (AI) is essential for maintaining a competitive edge. Our organization is committed to implementing AI-driven solutions to optimize our operations, improve predictive accuracy, and enhance customer satisfaction. This initiative will focus on optimization of predictions surrounding future engine maintenance, leveraging model training through diverse datasets and subject matter expertise.



Who Are You



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 machine learning, particularly in forecasting, predictive modeling, time series analysis, anomaly detection, and Natural Language Processing (NLP). You possess strong Machine Learning Engineering (MLE) and Software Engineering (SWE) principles to drive end-to-end development and deployment of AI solutions. You have a deep understanding of metrics and evaluation practices and 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 towards learning new applied domains, especially in aerospace or manufacturing, and your ability to communicate technical concepts clearly make you a valuable team player. You are enthusiastic about collaborating across interdisciplinary teams to achieve excellence.



What You Will Be Doing



In this role, you will be instrumental in developing, refining, and operationalizing high-quality AI products for Pratt & Whitney Canada. Your work will focus on creating predictive models for various AI modules (such as time on wing, part replacement rate, parts trending, schedules and unscheduled removals) by analyzing time-series sensor data. You will also develop text processing and NLP components for tasks like document data extraction and deriving insights from user feedback (free text). You will explore and implement a range of machine learning 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 contribute to developing strategies for failure labeling and defining appropriate time windows for model training and prediction. Furthermore, you will help establish a strong AI governance framework compliant with PW&C 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 efforts will directly contribute to enhancing Pratt & Whitney Canada's maintenance strategies, operational efficiency, and data-driven decision-making.



Required Skills / Expertise



We're looking for a talented and enthusiastic individual with a solid knowledge of machine learning, strong MLE and SWE principles for end-to-end development and deployment, and demonstrated experience in applied settings. Expertise with forecasting, predictive modeling, time series analysis, and Natural Language Processing (NLP) is crucial. You should have a deep understanding of metrics and evaluation practices and the capacity to contextualize scientific metrics for business needs.



Key Responsibilities:


Develop, refine, and operationalize high-quality AI products, including predictive models for various AI modules (e.g., time on wing, part replacement rate, parts trending, scheduled/unscheduled removals) using time-series sensor data. Develop and implement text processing and NLP components for tasks such as data extraction from TechPub/SB documents and analysis of user feedback. Design, implement, optimize, and evaluate machine learning models tailored for predictive maintenance, anomaly detection, and text analysis. Prepare and curate high-quality datasets (including time series and textual data) for model training and validation from diverse sources. Utilize state-of-the-art machine learning frameworks and tools (e.g., TensorFlow, PyTorch, Scikit-learn, Pandas) to enhance model performance and streamline data processing. Collaborate with cross-functional teams to build and deploy AI solutions that address client needs, ensuring seamless integration into existing systems and supporting the industrialization of models. Establish and maintain a strong AI governance framework compliant with PW&C security and AI best practices. Participate in the experimentation, piloting, and continuous improvement of developed AI solutions. Engage in regular client meetings, contributing insights and updates on model performance and project milestones through presentations and detailed reports. Optimize machine learning pipelines for efficient and scalable analysis, leveraging techniques relevant to time series (e.g., ARIMA, LSTM, matrix profiling) and NLP.


Required Qualifications:


Completion of a graduate level program or higher (M.Sc/Ph.D) in Computing Science, ML or Engineering Research or project experience in time series analysis, forecasting, predictive modeling, anomaly detection, and predictive maintenance use cases. Research or project experience in Natural Language Processing (NLP). Strong understanding and application of Machine Learning Engineering (MLE) and Software Engineering (SWE) principles for end-to-end model development and deployment. Proficient in Python programming language and related ML frameworks, libraries, and toolkits (e.g., Scikit-learn, TensorFlow, PyTorch, Pandas). A positive attitude towards learning and understanding new applied domains. Deep understanding of metrics and evaluation practices and the capacity to contextualize scientific metrics for business needs. Must be legally eligible to work in Canada.

Preferred Qualifications:


Previous experience applying machine learning to time series data for predictive maintenance problems, particularly in aerospace or manufacturing. Experience with deploying machine learning models in production environments. Strong software engineering (or MLE) skills. Experience with advanced time series techniques (e.g., ARIMA, LSTM, matrix profiling) and NLP models/frameworks. Familiarity with sensor data characteristics and challenges in an industrial context. Experience with AI governance frameworks and model industrialization processes (e.g., MLOps).

Non-Technical Requirements:


Desire to take ownership of a problem and demonstrated leadership skills Interdisciplinary team player enthusiastic about working together to achieve excellence Capable of critical and independent thought Able to communicate technical concepts clearly and advise on the application of machine intelligence Intellectual curiosity and the desire to learn new things, techniques, and technologies




Why You Should Apply



Besides gaining industry experience, additional perks include:


Work under the mentorship of an Amii Fellow and Amii Scientist for the duration of the project Participate in professional development activities Gain access to the Amii community and events Build your professional network The opportunity for an ongoing machine learning role at the client's organization at the end of the term (at the client's discretion)




About Amii



One of Canada's three main institutes for artificial intelligence (AI) and machine learning, our world-renowned researchers drive fundamental and applied research at the University of Alberta (and other academic institutions), training some of the world's top scientific talent. Our cross-functional teams work collaboratively with Alberta-based businesses and organizations to build AI capacity and translate scientific advancement into industry adoption and economic impact.



How to Apply



If this sounds like the opportunity you've been waiting for, please don't wait for the closing July 8, 2025 to apply - we're excited to add a new member to the Amii team for this role, and the posting may come down sooner than the closing date if we find the right candidate before the posting closes! When sending your application, please send your resume and cover letter indicating why you think you'd be a fit for Amii. In your cover letter, please include one professional accomplishment you are most proud of and why.



Applicants must be legally eligible to work in Canada at the time of application.



Amii is an equal opportunity employer and values a diverse workforce. We encourage applications from all qualified individuals without regard to ethnicity, religion, gender identity, sexual orientation, age or disability. Accommodations for disability-related needs throughout the recruitment and selection process are available upon request. Any information provided by you for accommodations will be kept confidential and won't be used in the selection process.