Machine Learning Scientists in the Department of National Defence apply advanced computational techniques and statistical methods to solve complex defence and security challenges. You will design, develop, and implement machine learning models that process large datasets to identify patterns, make predictions, and support decision-making across DND operations. Your work bridges theoretical research and practical application, contributing to innovations in areas such as cybersecurity, logistics optimization, threat detection, and operational analysis. As a Machine Learning Scientist, you will collaborate with interdisciplinary teams including software engineers, data analysts, subject matter experts, and military personnel to translate defence requirements into actionable AI solutions. You will conduct research, prototype new approaches, validate model performance, and document findings for peer review and operational deployment. The work environment is dynamic and intellectually challenging, combining independent research with team-based projects in a secure government setting.
Key Responsibilities
Contribute to artificial intelligence (ai) research & modeling projects and initiatives, Develop, test, and deploy AI/ML models and solutions, Analyze data to support evidence-based decision-making, Document technical approaches and ensure responsible AI practices
Required Skills
Python/R programming, Machine learning frameworks, Data analysis, Statistical modelling, Critical thinking, Technical proficiency, Attention to detail, Collaboration, Continuous learning
Typical Education
Post-secondary education or equivalent experience relevant to the position
Training
A Master's degree in Machine Learning, Computer Science, Statistics, Mathematics, or a related field is typically required, with a strong foundation in linear algebra, probability, and calculus. A Bachelor's degree in these disciplines with substantial professional experience in machine learning may be considered. Essential technical competencies include proficiency in Python, R, or similar languages; experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn; and knowledge of statistical modeling, data preprocessing, and model evaluation techniques. Familiarity with big data technologies, cloud computing platforms, and version control systems is valuable. Government of Canada security clearance at the Secret or Top Secret level is required for most positions. Professional development opportunities include participation in DND-sponsored research conferences, advanced training in specialized AI domains, collaboration with academic institutions, and continuing education in emerging technologies. Certifications in machine learning, cloud platforms, or specialized AI tools are encouraged and supported through professional development budgets.
Entry Plans
Entry into the Machine Learning Scientist career in the Public Service typically occurs through advertised competitions at the CR-03 or CR-04 levels (Research Officer classifications), or through talent pools maintained by DND and other federal departments. Many positions are filled through open competitions posted on the Government of Canada Job Bank. Recent graduates or those early in their careers may enter through the Federal Student Work Experience Program (FSWEP), the Post-Secondary Recruitment Campaign (PSRC), or the Co-op Student Program, which can lead to indeterminate positions. Lateral transfers from other federal departments with AI or research capabilities are common, as are deployments or assignments from other DND branches. Candidates with relevant specialized expertise may be recruited directly through targeted recruitment initiatives. All candidates must be Canadian citizens, pass security screening, and meet the language requirements for the position (typically English or French, or bilingual depending on the role and location).
Part-Time Options
Machine Learning Scientists in DND typically work full-time, permanent positions given the specialized nature and security requirements of the work. However, flexible work arrangements including telework are increasingly available, particularly for research and development phases of projects. Many positions allow for hybrid work schedules combining office-based collaboration with remote work days. Part-time or casual employment opportunities are limited in this classification but may occasionally be available for short-term contract positions or specific project-based work. Flexible hours may be negotiated within standard Public Service parameters to accommodate work-life balance, though project deadlines and operational needs may require extended hours during critical phases. Employees are encouraged to discuss flexible arrangements with their managers within the operational requirements of DND and the security protocols governing their work environment.
Related Careers
No related military careers on file for this position.
