Engineering

Montreal (Quebec)

19060BR

About the role

The Machine Learning Engineer is a senior member of Lockheed Martin Canada's Artificial Intelligence and Machine Learning (AI/ML) team and reports directly to the AI/ML Program Manager. Their primary responsibility is to develop the fundamental technologies and approaches for training and deploying proprietary AI models that underpin our flagship products. This includes designing and building robust data pipelines, selecting and tuning machine learning algorithms, and creating scalable model deployment flows that integrate seamlessly with existing software stacks.

The position requires a minimum of two days per week in the office to collaborate with cross-functional stakeholders such as data scientists, software architects, and DevOps engineers, to ensure that AI solutions meet both technical and operational requirements. The engineer will also accept enriched assignments that will expand the growth of our activities across multiple departments, such as supporting internal research and development, establishing best practices and guidelines for all users, and contributing to process and tool improvements to support organizational excellence.

In addition to core development work, the candidate must monitor model performance in production, implement continuous learning pipelines, and provide technical guidance to team members. This position offers a unique opportunity to shape the AI strategy for Lockheed Martin while working in a collaborative and dynamic environment that values innovation and cross-functional teamwork.

What you bring to the position

• Bachelor's degree from a recognized university in computer science, software engineering, mathematics, electrical engineering, or a related engineering discipline
• Relevant professional experience ranging from 5 to 10 years
• Experience in creating machine learning models with Python
• Experience using applied mathematics and statistical analysis in Python, i.e., backpropagation, activation functions, and optimization of cost functions
• Experience applying data science methodologies, i.e., feature extraction, synthetic data generation, and feature space reduction
• Expert knowledge of machine learning models, including neural network architectures (recurrent and convolutional neural networks), support vector machines, trees, regression, etc.
• Ability to define and apply novel and creative solutions to complex machine learning problems
• Experience in developing end-to-end Machine Learning Operations (MLOps) pipelines including typical training, testing, validation, data collection, and processing
• Ability to effectively communicate complex ideas, solutions, and issues to technical and non-technical audiences
• Ability to work autonomously as well as effectively develop collaborative projects within direct and cross-functional teams
• Ability to adapt and perform duties within a dynamic environment
• Experience in converting real-world systems, behaviors, and decision factors into mathematical and machine learning models that support realistic simulation and predictions
• Ability to design and evaluate, measure the performance of AI models in accordance with the scientific method
• Aptitude and ability to conduct academic research to stay abreast of the latest advances in artificial intelligence and related technologies
• In-depth understanding of machine learning libraries, i.e., NumPy, Pandas, CUDA, and Pytorch
• Adaptability to work in secure and restricted networks, i.e., without internet access or certain free and open-source libraries
• Able to obtain NATO