Machine Learning/AI Engineer (Vancouver)

Professional & Business Support Posted : May 7, 2026 Full-Time Reporting to Director, Data, the AI and Machine Learning Engineer is responsible for designing, building, and operating production grade machine learning systems that deliver measurable business outcomes. This is a senior individual contributor role requiring strong technical judgment, end to end ownership, and the ability to translate complex business problems into reliable, scalable AI solutions. The role partners closely with data engineering, software development, product, and business stakeholders while remaining accountable for the quality, performance, and sustainability of deployed ML systems. Design, develop, and deploy scalable machine learning models and AI systems across multiple business domains, including dynamic pricing, revenue management, forecasting, classification, recommendation systems, and natural language processing. Own the full machine learning lifecycle, from problem definition and data exploration through model training, evaluation, deployment, monitoring, and iteration in production. Build and productionize pricing and revenue models that balance revenue, margin, conversion, and regulatory constraints, ensuring models operate safely and reliably in live environments. Partner with data engineers to design and maintain robust data pipelines that support machine learning systems with high quality, reliable data inputs. Collaborate with product, pricing, and business stakeholders to translate requirements into technical solutions with clearly defined success metrics tied to business outcomes. A/B tests, causal inference, bandits) to evaluate real world impact and inform model improvements beyond offline performance metrics. Ensure strong model governance practices, including documentation, versioning, monitoring, and compliance with enterprise and regulatory standards. Monitor deployed models for performance degradation, bias, and drift, and implement retraining or mitigation strategies as required. Contribute to the evaluation and responsible adoption of emerging AI/ML techniques, tools, and platforms, including generative AI and foundation models. Provide technical mentorship, code reviews, and knowledge sharing to support team capability and engineering excellence, without direct people management accountability. Robust ownership mindset with accountability for delivering high quality, production ready ML systems. Ability to communicate complex technical concepts clearly to both technical and non technical audiences. Sound technical judgment when making trade offs between model performance, scalability, risk, and business impact. Curiosity and adaptability in exploring new techniques, tools, and approaches. 5+ years of hands on experience in machine learning engineering or a closely related role, including significant experience deploying ML systems into production environments. Strong proficiency in Python and modern ML frameworks and libraries (e.g., Experience deploying and operating ML models in cloud environments (AWS, Azure, or GCP), including containerization and model serving. Solid understanding of MLOps practices, including CI/CD for ML, model versioning, monitoring, and experiment tracking. Strong foundation in statistics, experimental design, and model evaluation. Experience with generative AI, LLMs, or agent based frameworks considered an asset. Hybrid working arrangements with 3 days work from office. The base salary offered for this role is $125,000 to $145,000 per annum and can vary based on job-related expertise, qualifications, experience and internal equity. Eligible for Armstrong Collective’s discretionary bonus program. Armstrong Collective supports our team members’ health and wellness by providing a comprehensive medical plan with 100% employer paid premiums. Short-term disability, long-term disability benefits, travel emergency assistance, vacation time and sick time, up to 5% RRSP and/or TSFA match, and two complimentary annual train tickets after first year of employment. We celebrate diversity and are committed to creating an inclusive environment for all team members. Apply on Kit Job: kitjob.ca/job/2ps045