Key skills
CloudMachine LearningMLMLOpsData EngineeringCI/CD
About this role
Role Overview
- 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
- Paid sabbatical
- Wellness and productivity spending account
- Parental program
- Events and activities
- Training and development
- And more…