About the role

The Machine Learning Engineer is a senior member of Lockheed Martin Canada’s AI and Machine Learning team and report directly to the AI/ML Program Lead. Their primary responsibility will be to develop the foundational 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 workflows that integrate seamlessly with existing software stacks.

The role requires a minimum of two days per week in the office to collaborate with cross‑matrix stakeholders such as data scientists, software architects and DevOps engineers, ensuring that AI solutions meet both technical and business requirements. The engineer will also take on stretch assignments that extend our business growth across multiple departments, such as supporting Internal Research and Development, establishing best‑practices and guidelines for all users, and contributing to process and tooling improvements in supporting enterprise excellence.

In addition to core development work, the candidate will be expected to 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 Canada while working in a collaborative, fast‑paced environment that values innovation and cross‑functional teamwork.

What you bring to the role

• Possess a Bachelor’s degree from an accredited university in computer science, software engineering, mathematics, electrical or a related engineering field.
• 5-10 years of relevant professional experience.
• Experience creating Machine Learning Models with Python
• Experience using applied mathematics and statistical analysis within Python, i.e. Backwards Propagation, Activation functions, and Cost function optimization.
• Experience with 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 Convolution Neural Networks), Support Vector Machines, trees, regression, etc.
• Ability to define and apply novel and creative solutions to complex ML problems.
• Experience with developing end-to-end MLOps pipelines which includes model training, testing, validation, data collection and processing.
• Ability to effectively communicate complex ideas and solutions and issues to both technical and non-technical audiences.
• Ability to work independently as well as effectively develop collaborate projects within direct and cross-functional teams.
• Ability to adapt and perform in a dynamic environment
• Experience with converting real-world systems, behaviors, and decision factors into mathematical and machine learning models that support realistic simulation, and predictions.
• Ability to design and assesses, measure AI model performance adhering to the scientific method.
• Aptitude and ability to conduct academic research to maintain state of the art awareness of artificial intelligences and related technologies.
• In-depth understanding of ML libraries, i.e. NumPy, Pandas, CUDA, and Pytorch.
• Adaptability to work in secure and restricted networks, i.e. no internet access, lack of access to some free and open source libraries.
• Eligibility to obtain NATO Secret clearance in a timely manner.

Additional skills desired for the rol