AI & Machine Learning Engineer, Level 17 or 18 803 EN

Application deadline: September:00PM ET

Join the EDC Team!

At EDC we support Canadian businesses to succeed globally. We provide the financial tools and expertise they need to explore new markets reduce risks all towards the goal of making Canada and the world better through trade.

Position: AI Machine Learning Engineer Level 17 or 18

Employment Type:Permanent

• Machine Learning Engineer 17: Salaries typically range from $84698 to $112931 annually based on qualifications and experiences plus a performance-based incentive.
• Machine Learning Engineer 18: Salaries typically range from $96557 to $128743 annually based on qualifications and experiences plus a performance-based incentive.

• Export Development Canada operates under a hybrid work model with employees currently required to work from the office two days per week. Effective September 2026 this requirement will increase to three days per week and will be implemented gradually through a phased approach based on employee location. (subject to change).
• This role can be performed from EDCs headquarters in Ottawa or from one of our Community Hubs located in Toronto or Montreal.
• Relocation assistance is available for candidates who meet the eligibility criteria.

Internal Employees please consult the ServiceNow article entitled Internal movements what you need to know.

At Export Development Canada (EDC) we empower Canadian businesses to succeed globally. As a financial Crown corporation we offer innovative financial solutions and expert insights to help businesses explore new markets mitigate risks and achieve growth.

• Comprehensive Benefits: EDC offers a competitive compensation & benefits package work-life balance & the opportunity to help make Canada and the world better through trade.
• Work-Life Balance: EDC offers a competitive compensation package & work-life balance. We have hybrid work options 3 to 4 weeks paid vacation a corporate closure period summer early Fridays & no meeting Fridays.
• Professional Development: Take advantage of our continuous learning opportunities including training programs workshops and language training.
• Inclusive Culture: Be part of a diverse and inclusive workplace that champions employment equity & values diversity of ideas strengths & backgrounds to succeed.
• Wellness Programs: Access to wellness initiatives mental health support and fitness programs to keep you healthy and happy.
• Community Engagement: Participate in volunteer opportunities and give back to the community through our various social responsibility programs.

The Digital & Technology Solutions (DTS) group under the leadership of the Chief Information Officer was established in 2023 with the mission of empowering our customers and colleagues to take on the world by seamlessly delivering secure and reliable digital experiences. Digital & Technology Solutions has set out to achieve the following objectives for EDC:

• Define execute and sustain the integrated technology target state target data model and technology operations required to enable EDCs 2030 business transformation.
• Establish and manage the rolling 3 Year Digital Roadmap that sequences the technology outcomes required to achieve the technology target state and facilitate its execution across all domains in the organization.
• Keep pace with industry trends and emerging technologies ensuring EDC has access to the digital technology tools it needs to stay relevant in the market and grow Canadian global trade.
• Lead and ensure integrated digital data infrastructure and cybersecurity implementations to create excellent customer user and employee experiences.

Why Join the AI Centre of Enablement

• Help shape how AI is responsibly scaled across EDC through enterprise-grade AI and machine learning solutions.
• Work on production AI products with real business impact not experimental projects.
• Influence AI strategy governance and delivery at a national institution.
• Collaborate with business SMEs data scientists architects and platform teams to move AI solutions from experimentation to production.
• Work across AI/ML engineering MLOps cloud platforms DevOps and Responsible AI practices.
• Contribute to model deployment CI/CD automation observability monitoring and governance in a modern AI environment.
• If selected for Level 17 the role builds deploys and supports production AI and machine learning solutions while working closely with senior engineers and architects. This role offers meaningful production responsibility and the opportunity to develop expertise across the full AI lifecycle with a clear growth path toward the ownership leadership and strategic scope expected at Level 18.
• If selected for Level 18 the role takes ownership of the end-to-end AI lifecycle from production engineering and platform operations to governance scalability and ongoing optimization. As a senior engineer you will help shape enterprise AI standards lead the transition to product-based AI delivery and drive the reliability security and compliance of production AI systems while influencing how AI is delivered across EDC.

How do we Build AI at EDC

At EDC AI solutions are built and operated using standardized enterprise-grade engineering practices designed to ensure reliability security scalability and responsible use. All production AI systems follow governed design patterns rigorous evaluation and observability requirements documented architecture decisions secure-by-design data handling practices and structured promotion processes for models and prompts. While these standards apply at both levels Level 18 engineers are expected to help shape and strengthen these practices whereas Level 17 engineers apply them under guidance while building toward greater ownership and accountability.

• Design and maintain reusable ML assets including feature pipelines shared components deployment patterns and evaluation frameworks to strengthen organizational AI maturity.
• Collaborate with data scientists architects platform and security teams to transition models from research to scalable reliable production services.
• Additional responsibilities - Level 17:
• Contribute to the engineering and deployment of production-grade ML and GenAI solutions including batch and real-time inference patterns using the same standardized enterprise deployment models.
• Support the AI system lifecycle (MLOps / LLMOps / AgentOps) including versioning monitoring and retraining support escalating scaling rollback and retirement decisions to senior engineers where they carry significant risk.
• Support GenAI applications (RAG-based and agentic patterns) applying evaluation and guardrail patterns established by senior engineers and contributing to their improvement.
• Apply security governance and Responsible AI controls by design working within platform standards Protected B requirements auditability and risk-based controls set by the team.
• Contribute to CI/CD pipelines Infrastructure as Code and standardized environment promotion across experimentation staging and production.
• Monitor AI system health and diagnose issues including performance degradation data and model drift and cost anomalies escalating and supporting remediation of production incidents within defined SLAs.
• Build basic machine learning algorithms and support the creation of more complex algorithms that identify patterns in structured data partnering with business stakeholders to ensure data is collected in accordance with model standards.
• Provide fault isolation and initial resolution for complex challenges working within diagnostic approaches designed by senior engineers; produce multiple concepts and prototypes in support of new AI product and service ideas.
• Analyze specific well-defined problems and issues to identify and evaluate the best available technical solution.
• Additional responsibilities - Level 18:
• Engineer and deploy production-grade ML and GenAI solutions including batch real-time and event-driven inference patterns using standardized enterprise deployment models primarily in Databricks platform and within Azure cloud ecosystem.
• Own the full AI system lifecycle (MLOps / LLMOps / AgentOps) including versioning monitoring retraining scaling rollback and retirement of production models.
• Operationalize GenAI applications (RAG-based and agentic patterns) embedding evaluation guardrails and cost awareness as core design principles.
• Embed security governance and Responsible AI controls by design ensuring compliance with platform standards Protected B requirements auditability and risk-based controls.
• Automate AI delivery and operations through CI/CD pipelines Infrastructure as Code and standardized environment promotion across experimentation staging and production.
• Monitor diagnose and remediate AI system health including performance degradation data and model drift bias indicators cost anomalies and production incidents within defined SLAs.
• Build and validate predictive descriptive and behavioural models that link directly to business performance indicators working with business SMEs to translate insight into actionable recommendation - not just a shipped model.
• Create complex algorithms that identify patterns in structured data through supervised and unsupervised learning and manage data preparation in close collaboration with business stakeholders and internal clients.
• Apply strong engineering judgment to balance performance scalability cost security and risk in enterprise AI systems operating at scale.

• University degree in Computer Science Engineering Mathematics Data Science or a related technical discipline.
• Level 17:
• Minimum 5 years of experience in AI and ML engineering roles delivering production systems in enterprise environments.
• Minimum 5 years of experience designing or contributing to large-scale data platforms supporting batch and real-time workloads primarily in Databricks platform and within Azure cloud ecosystem.
• Minimum 3 years of hands-on experience building and operating ML or AI systems in production including monitoring retraining and incident response.
• Minimum 3 years of experience working with cloud platforms including deployment automation networking and security services via Azure cloud ecosystem with focus on Databricks data operations.
• Minimum 3 years of experience implementing CI/CD pipelines and Infrastructure as Code for ML/AI workloads.
• Minimum 3 years of experience developing production-grade code using Python and data-centric languages (e.g. SQL Java Scala).
• Minimum 3 years of experience operating within formal IT service management and Agile delivery environments including incident/change management and cross-functional delivery.
• Minimum of 1 year of applied experience with GenAI or MLOps concepts including LLMs RAG-based architectures or agentic/workflow-oriented patterns in a production context.
• Level 18:
• Minimum 7 years of experience in AI and ML engineering roles delivering production systems in enterprise environments.
• Minimum 7 years of experience designing or contributing to large-scale data platforms supporting batch and real-time workloads primarily in Databricks platform and within Azure cloud ecosystem.
• Minimum 7 years of hands-on experience building and operating ML or AI systems in production including monitoring retraining and incident response.
• Minimum 7 years of experience working with cloud platforms including deployment automation networking and security services via Azure cloud ecosystem with focus on Databricks data operations.
• Minimum 7 years of experience implementing CI/CD pipelines and Infrastructure as Code for ML/AI workloads.
• Minimum 5 years of experience developing production-grade code using Python and data-centric languages (e.g. SQL Java Scala).
• Minimum 7 years of experience operating within formal IT service management and Agile delivery environments including incident/change management and cross-functional delivery.
• Minimum 3 years of applied experience with GenAI or MLOps concepts including LLMs RAG-based architectures or agentic/workflow-oriented patterns in a production context.

• Experience deploying containerized AI workloads and operating scalable cloud-based infrastructure.
• Demonstrated ability to collaborate across multidisciplinary teams communicate complex technical concepts clearly and operate effectively in complex technical environments.
• Familiarity with industry AI security governance and risk frameworks and how they are applied including concepts aligned to the Databricks AI Security Framework (DASF) and recognized standards and guidance such as:
• MITRE ATLAS (AI threat landscape) & MITRE ATT&CK;
• OWASP LLM Top 10 (2025) and OWASP ML Top 10 (v0.3);
• ISO/IEC 42001:2023 (AI Management Systems) ISO/IEC 27001:2022 (Information Security);
• NIST SP 800-53 Rev. 5 HITRUST ENISA Securing ML Algorithms and the EU AI Act;
• CAN/DGSI 101:2025 (Ethical Design and Use of AI by Small & Medium Organizations).
• Bilingual in both official languages (English and French).
• Level 17:
• Degree with a strong analytical or technical concentration e.g. a specialization in Machine Learning Statistics or Applied AI within a broader Computer Science or Engineering program.
• Relevant industry certifications at the Associate tier such as Databricks Data Engineer Associate Databricks GenAI Engineer Associate Azure AI Engineer Associate Azure DevOps Engineer Expert or Agile certifications (e.g. DASM).
• Hands-on exposure to the enterprise ML/AI Databricks Platform and/or Azure AI Foundry including Git-based development workflows.
• Contribution to production or near-production GenAI solutions in Databricks and/or Azure including RAG-based or agentic patterns.
• Exposure to model or LLM evaluation telemetry or feedback-loop tooling in support of safe and reliable AI operations.
• Level 18:
• Advanced education such as a Masters degree in Artificial Intelligence Data Science Computer Science Engineering or a closely related field.
• Relevant industry certifications such as Databricks Data Engineer Databricks GenAI Engineer Azure AI Engineer Associate Azure Solutions Architect Expert Azure DevOps Engineer Expert Azure Security Engineer cloud security (e.g. CCSP) and/or Agile certifications (e.g. DASM).
• Hands-on experience with enterprise ML/AI Databricks Platform & Azure AI Foundry including model lifecycle management and Git-based development workflows.
• Demonstrated delivery of production GenAI solutions in Databricks & Azure including RAG-based and/or agentic patterns with embedded evaluation and guardrails.
• Experience implementing model and LLM evaluation telemetry and feedback loops to support safe and reliable AI operations in both platforms: Databricks & Azure.
• Experience working with external vendors in managed-service or enterprise delivery environments.

EDC is committed to Fair Employment Practices and preference will be given to a candidate who is able to work legally in Canada at the time of application (Canadian Citizens or Permanent Residents). Candidates must meet the requisite government security screening requirements. Internal applicants must also meet EDCs eligibility criteria for applying to internal opportunities. For more information please refer to Section 2.1 in the Talent Acquisition Standard available on LINK under the Resources tab in the Policies & Procedures section.The position is open to those who meet all of the essential requirements stated above and whose applications are received by the closing position is open to those who meet all of the essential requirements stated above and whose applications are received by the closing date.

This position is open to individuals who meet all the essential criteria outlined above and submit their applications by the closing date. Ready to make a difference This is your chance to join a dynamic growing team and leave your mark on our organization development finance and the world.

Apply today!

Want to learn more about EDC Check our website at

Export Development Canada (EDC) is dedicated to fostering employment equity and building a diverse workforce. We are committed to creating a safe and inclusive environment that respects people from all cultures backgrounds and abilities. At EDC we nurture a culture of inclusion and belonging where everyone has equal opportunity to grow develop succeed and be their truest selves.

We actively encourage applications from women Indigenous peoples visible minorities persons with disabilities and members of the 2SLGBTQI community.

Your application must clearly demonstrate how you meet all the requirements. We thank all applicants interest in a career at EDC; however only those selected for an interview will be contacted. Please note that qualified candidates may be considered for similar roles at this level within EDC.

EDC recognizes that disclosing the need for accommodations can be a personal matter. Please know that as an organization we are committed to maintaining confidentiality and ensuring that any accommodations provided are tailored to support your needs. Our aim is to ensure you have a comfortable and positive experience throughout the recruitment process so please do not hesitate to contact us directly for any accommodation requests at . We are here to support you every step of the way.

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