Design, develop and deliver scalable software, data and machine learning solutions for client projects
Identify solutions to cross-cutting problems using your experience in software development, data engineering and MLOps
Design, plan and implement data pipelines, ML workflows and the cloud or on-premises infrastructure that supports them
Develop end-to-end solutions aligned with specifications and documentation
Build and improve CI/CD pipelines, data pipelines, model deployment workflows and automation practices
Contribute to containerized, virtualized and cloud-native environments that support data and ML workloads
Support modernization initiatives by improving architecture, testing, deployment, observability, data quality and maintainability
Define, document and communicate non-functional requirements such as performance, reliability, security, scalability and maintainability
Support practices related to the ML lifecycle, such as experiment tracking, model versioning, validation, deployment, promotion, rollback and monitoring
Mentor colleagues on best practices in software development, data engineering, MLOps and delivery
Take initiative, own your deliverables end-to-end and manage priorities effectively
Maintain and strengthen quality standards and best practices in software development
Research, test and adopt new techniques, tools and technologies
Advise clients on technical direction, trade-offs, architecture, data platforms and ML solution design
Requirements
5+ years of software development experience, including recent, hands-on experience in data engineering, MLOps or production ML systems
Bachelor's degree, college diploma, certification in a software-related field, or equivalent experience
Intermediate or conversational French at minimum
Strong backend development experience
Good technical judgment and ability to make pragmatic architectural decisions
Experience building or supporting data pipelines, data platforms or ML deployment workflows
Experience collaborating directly with clients or stakeholders
Ability to mentor team members and contribute to the quality of technical delivery
Comfortable working in ambiguous contexts and able to bring structure to complex problems
Tech Stack
Cloud
Benefits
Competitive salary and contribution to your retirement savings plan (RRSP)
Flexible schedule and autonomy in how you work
Ability to work from anywhere for up to 8 weeks per year