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AI/Machine Learning Engineer

Armstrong Collective
Vancouver, BC

Postuler dès maintenant

Détails du poste

Permanent
De 125 000 $ à 145 000 $ par an

Profil recherché

TensorFlow
CI/CD
Azure
PyTorch
Google Cloud Platform
AWS
Apprentissage automatique
Traitement du langage naturel
Intelligence artificielle
Évaluation de modèle
Python

Description complète du poste

Purpose

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.

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, 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

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

Strong 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

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

Eligible Benefits

Armstrong Collective supports our team members’ health and wellness by providing a comprehensive medical plan with 100% employer paid premiums, some of which includes:

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

Armstrong Collective, Rocky Mountaineer and Canyon Spirit are an equal opportunity employer, driven by our values of creating meaningful moments, being one team, and achieving extraordinary outcomes. Our strong company culture supports our vision of a diverse, open, safe, and respectful workplace. 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.

Please ensure to opt-in for text messages when you apply in order to receive interview updates.

#ArmstrongCollective

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