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
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:
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.
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#ArmstrongCollective
Our reason for working at Rocky Mountaineer is simple – to be the creators of life changing experiences, not just for our guests, but also for our employees. Join us at Rocky Mountaineer and build your career alongside an incredibly talented global team of passionate, energetic, diverse, and fun individuals who have helped to position us as the world-renowned leader in luxury train travel.
With rail routes operating in Western Canada and the American Southwest, Rocky Mountaineer’s team stretches the globe with employees in Canada (BC, AB, ON, QC), the USA, the UK, Australia and New Zealand.
Rocky Mountaineer has received numerous international awards and accolades. We have won thirteen World Travel Awards throughout our history; we were named Best Sustainable Train in 2021 in the Lonely Planet's Best in Travel awards; and are three-time winner of the Best Rail Company category at the Globe Travel Awards. We have been named one of Canada’s Top Small and Medium Employers three years in a row and three-time winner of BC’s Top Employer title. In 2023, we were recognized as a Platinum winner for Deloitte Canada's Best Managed Companies awards program - we have been recognized as a Best Managed Company since 2014 and achieved the award's Gold Standard five times.
