AI/Machine Learning Engineer (North Vancouver)

Overview

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.

Key Responsibilities

• Design, develop, and deploy scalable machine learning models and AI systems across multiple business domains, including dynamic pricing, revenue management, forecasting, classification, recommendation systems, & 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.
• Design and execute experiments (e.g., 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.

What You Bring

• Strong 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.
• Resilience and persistence when solving ambiguous, high impact problems.

Experience & Qualifications

• 5+ years of hands on experience in machine learning engineering or a closely related role, including significant experience deploying ML systems into production environments.
• Solid proficiency in Python and modern ML frameworks and libraries (e.g., scikit-learn, PyTorch, TensorFlow, gradient boosting frameworks).
• 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.

Work Environment

Eligible to work in Canada.
Hybrid working arrangements with 3 days work from office.

Compensation & Benefits

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 Collectives discretionary bonus program.
• Comprehensive medical plan with 100% employer paid premiums, including medical, dental, vision, life insurance.
• Short term disability, long term disability benefits.
• Travel emergency assistance.
• Vacation time and sick time.
• Up to 5% RRSP and/or TSFA match.
• Two complimentary annual train tickets after first year of employment.

EEO Statement

Armstrong Collective is an equal opportunity employer, driven by our values of creating meaningful moments, being one team, and achieving extraordinary outcomes. We celebrate diversity and are committed to creating an inclusive environment for all team members. If you require any accommodation during the application process or throughout your employment, please let us know. We will work with you to ensure your needs are met and to create a supportive environment.