Senior Machine Learning Engineer (AI)

Location: Vancouver, British Columbia, Canada; Flex work with at least 50% of each quarter spent in the office or in the field

Annual base salary: CAD 156,000–234,000, varying by work location; additional bonus or commission and annual refresh stock grants may apply.

Company

hirify.global is a Fortune 500 company and AI platform for managing people, money, and enterprise operations.

What you will do

• Design, develop, and deploy scalable predictive, Generative AI, and LLM-powered systems for core enterprise applications.
• Own the full ML lifecycle, including data extraction, feature engineering, training, deployment, optimization, and production monitoring.
• Partner with data scientists, software engineers, product managers, and UX designers to translate business problems into AI solutions.
• Establish engineering best practices, robust MLOps processes, and optimized code for high-scale production environments.
• Mentor junior engineers, conduct code and architecture reviews, and contribute to the technical roadmap.
• Ensure models meet standards for data privacy, security, fairness, and responsible AI.

Requirements

• For the Senior Machine Learning Engineer level: 7+ years of industry software engineering experience focused on applied machine learning, deep learning, or NLP.
• Expert-level Python proficiency and strong foundations in data structures, algorithms, and object-oriented design.
• Deep hands-on experience with machine learning and deep learning libraries such as PyTorch, TensorFlow, Scikit-learn, and Hugging Face.
• Experience deploying ML models from research or notebook environments into scalable, high-traffic production systems.
• Experience with AWS or GCP and modern infrastructure tools including Docker and Kubernetes.
• Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or another highly quantitative field, or equivalent practical experience.
• Applicants may also qualify at the Machine Learning Engineer level with 5+ years of industry software engineering experience focused on applied machine learning, deep learning, or NLP.

Culture & Benefits

• Flex Work combines remote flexibility with in-person collaboration; at least half of each quarter is spent in the office or in the field, depending on the role.
• Work with cross-functional AI, product, data science, and engineering teams on production-grade systems used at global enterprise scale.
• Access to tools, professional development, and long-term employee support.
• Potential eligibility for a bonus plan or role-specific commission/bonus, annual refresh stock grants, and comprehensive benefits.
• Reasonable accommodations are available during the application process.