Key skills
PythonAIMachine LearningMLLLMMLOpsData EngineeringAgileLeadershipCloud Security
About this role
We are looking for Senior Cloud Engineer - AI/ML for our client in Toronto, ON
Job Title: Senior Cloud Engineer - AI/ML
Job Type: Contract
Job Overview:
- We are seeking a Senior Cloud Engineer with expertise in AI/ML to design, implement, and scale cloud-based machine learning platforms.
- The ideal candidate will lead AI/ML service enablement, build MLOps pipelines, and ensure secure, compliant, and efficient deployment of AI solutions across cloud environments.
Responsibilities:
- Evaluate and enable AI/ML services across cloud platforms through proof-of-concepts and technical assessments.
- Design and implement reusable architectural patterns for secure AI/ML integrations.
- Build end-to-end MLOps platforms and automated pipelines for model lifecycle management.
- Develop infrastructure-as-code frameworks and automation to accelerate AI/ML adoption.
- Produce technical documentation covering security, networking, compliance, and cost analysis.
- Implement observability solutions including model monitoring, metrics, and drift detection.
- Collaborate with enterprise architecture and stakeholders to align solutions with strategic goals.
- Provide technical leadership and mentorship on cloud and AI/ML best practices.
Requirement/Must Have:
- 5 7 years of cloud engineering experience with at least 3 years focused on AI/ML platforms.
- Strong hands-on expertise with cloud-based AI/ML services.
- Experience building MLOps platforms and automated ML pipelines.
- Strong knowledge of LLM lifecycle management, agent-based AI, retrieval-augmented generation, and prompt engineering.
- Experience implementing governance and guardrails for AI/ML systems.
- Proficiency in Python and infrastructure-as-code tools.
- Experience with model tracking and registry tools.
- Strong understanding of cloud security patterns including network isolation and encryption.
- Experience with cloud networking architecture in regulated environments.
- Experience working in compliance-driven industries.
- Experience working in Agile environments.
Should Have:
- Cloud AI/ML certifications.
- Experience with vector databases and embedding models.
- Knowledge of model optimization and inference acceleration.
- Experience in financial services or banking domains.
Skills:
- Cloud architecture and AI/ML engineering.
- MLOps and pipeline automation.
- Infrastructure as code and cloud security.
- Model monitoring and observability.
- Data engineering and AI integration.
Qualification And Education:
- Bachelor s or Master s degree in Computer Science, Engineering, or a related field.