As an MLOps Engineer with the Department of National Defence, you will bridge the gap between machine learning development and operations by designing, deploying, and maintaining machine learning systems at scale. You will work with data scientists, software engineers, and stakeholders to transform experimental machine learning models into reliable, production-ready solutions that support defence and security operations. This role combines software engineering best practices with machine learning expertise to ensure that AI systems are robust, scalable, and aligned with organizational needs.
Your responsibilities will include developing and maintaining machine learning pipelines, automating model deployment processes, monitoring system performance, and troubleshooting issues in production environments. You will collaborate with cross-functional teams to establish best practices for model versioning, data management, and system reliability. You may also contribute to infrastructure planning, security assessments, and documentation to ensure compliance with Government of Canada standards and DND operational requirements.
You will work in a dynamic, evolving field where continuous learning is essential. Your work environment may include both office-based collaboration and remote work options, with opportunities to engage with leading-edge AI technologies and contribute to projects with meaningful impact on national defence and security.
Key Responsibilities
Contribute to artificial intelligence (ai) engineering & deployment 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
To succeed as an MLOps Engineer, you typically need a bachelor's degree in computer science, software engineering, mathematics, or a related field. Relevant certifications in cloud platforms (AWS, Azure, Google Cloud), containerization technologies (Docker, Kubernetes), or machine learning frameworks are highly valued. Strong proficiency in programming languages such as Python, Java, or Go is essential, along with hands-on experience with version control systems, CI/CD pipelines, and data engineering tools.
Professional development opportunities within DND include training in advanced machine learning operations, cloud architecture, cybersecurity, and Government of Canada specific tools and policies. The Public Service offers learning programs through the Canada School of Public Service and partnerships with industry leaders. You may pursue certifications such as Certified Kubernetes Administrator (CKA), AWS Certified Machine Learning, or similar credentials. Ongoing professional development ensures you remain current with rapidly evolving technologies and industry standards while supporting DND's AI transformation initiatives.
Entry Plans
You can enter this career path through several routes within the Government of Canada. The primary pathway is through open competitions advertised on the Government of Canada Job Bank and the DND civilian careers website. Depending on your experience level, you may apply for positions at different classification levels (typically IT-03 or IT-04 for entry and intermediate roles).
If you are a recent graduate, consider the Federal Student Work Experience Program (FSWEP) or Post-Secondary Recruitment Campaign (PSRC) to gain initial federal government experience. The Public Service can also hire qualified candidates through bridging programs or lateral moves from other government departments with similar IT or AI roles. Some positions may be filled through talent pools or priority hiring initiatives focused on emerging technology areas. Candidates with prior military service or security clearances may have additional advantages. For specific opportunities, regularly check the DND careers website and subscribe to job alerts matching your qualifications.
Part-Time Options
MLOps Engineer positions at DND typically offer flexible work arrangements to support work-life balance and attract top talent in this competitive field. Many roles provide options for hybrid work, combining office-based collaboration with remote work days, particularly as cloud-based tools and virtual collaboration platforms are standard in this field.
Full-time permanent positions are the primary offering; however, some project-based or term positions may provide flexibility in scheduling. Telework eligibility depends on the specific role, team requirements, and security considerations. DND supports flexible work arrangements within operational needs, and discussions about flexible schedules can occur during the hiring process or after employment begins. Employees in this role may also have access to compressed work weeks or other arrangements negotiated with their management. Benefits of federal employment, including leave provisions and work-life balance programs, apply to all eligible positions. For detailed information about flexibility options for a specific role, contact the hiring manager or DND HR representative during the application process.
Related Careers
No related military careers on file for this position.
