Senior Software Developer responsible for designing and developing solutions in data engineering and machine learning. Collaborating with teams to deliver scalable software solutions with agile methodologies.
Responsibilities
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
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
Lead AI/ML & MLOps Engineer executing projects from data foundations to model deployment. Collaborating with sales to drive AI/ML engagements for our clients.
Applied ML Engineer working on AI - driven insights at Kaseya. Collaborating with product teams to enhance features with machine learning and data analysis.
Adversarial Machine Learning Engineer conducting adversarial testing and simulations on LLM - driven AI systems for enterprise security. Collaborating with teams to validate and document findings.
MLOps Engineer managing infrastructure for large 2D and 3D media datasets at NBCUniversal. Responsible for automation, reproducibility, and performance of machine learning lifecycles.
Senior ML Engineer leading the strategic direction of machine learning infrastructure for global food delivery platform. Collaborating with Data Science team for seamless model deployment and innovation.
Machine Learning Intern/Co - op at Cohere working on developing and training models for AI applications. Join a team focused on advancing AI technology in an inclusive environment.
Machine Learning Engineer designing and deploying detection ML systems for social engineering defense platform at Doppel. Collaborating to mitigate evolving digital threats using AI.
Senior ML Engineer responsible for designing and building ML pipelines for a Trust Scoring platform. Involves productionizing models and implementing MLOps best practices.
Principal Machine Learning Engineer designing the core ML systems for AI agents at Workday. Collaborating in cross - functional teams to integrate ML solutions into the platform.
Staff Machine Learning Research Developer at D - Wave enabling quantum machine learning methods. Researching and developing software to enhance quantum computing capabilities for optimization and AI.