Senior Machine Learning Engineer

Location: In office in Toronto, 8 Spadina Ave

Company

hirify.global operates a global advertising supply-side platform that processes real-time programmatic auctions at internet scale.

What you will do

• Design and implement enterprise-scale MLOps systems covering data ingestion, feature pipelines, model training, validation, deployment, and monitoring.
• Productionalize and support scalable, efficient machine learning models and solutions.
• Define standards for model versioning, lifecycle management, monitoring, alerting, traceability, and highly available low-latency inference.
• Improve data management strategies and performance for extensive data loads and distributed systems.
• Mentor engineering teams on machine learning deployment practices and contribute to technology strategy.
• Enable safe deployment approaches, including shadow deployments, canary releases, and gradual rollouts.

Requirements

• Advanced degree in Computer Science, Engineering, or a related field, or equivalent experience.
• Expertise in high-performance backend technologies, preferably including Golang.
• Extensive experience with cloud or on-premises distributed systems, data-intensive applications, and large-scale backend design.
• Deep knowledge of machine learning operationalization, tools, frameworks, and current practices.
• Experience developing, deploying, and continuously improving complex CI/CD pipelines.
• Strong problem-solving skills and the ability to develop solutions for sophisticated technical challenges.

Culture & Benefits

• Full-time employment with health, dental, and vision coverage for employees and dependents.
• Paid time off, health days, personal obligation days, and flexible work schedules.
• Retirement matching, equity packages, parental leave, and an annual well-being allowance.
• Commuter benefits, employee assistance, mental health support, and wellness activities.
• Volunteer time off, donation matching, continuous learning resources, town halls, and community-led events.
• Work in an engineering-first culture focused on internet-scale systems and inclusive collaboration.