Senior Machine Learning Engineer, Professional Services – Amazon – Vancouver, BC / Montreal, QC / Calgary, AB / Toronto, ON
Location: Calgary, AB | Company: Amazon
Amazon Web Services (AWS) is hiring a Senior Machine Learning Engineer to build and operationalize ML/DL solutions that help large enterprises realize business value from AI/ML on AWS. In this customer-facing role, you’ll collaborate with Data Scientists, Data Engineers, and Architects to deliver end-to-end platforms—from data preparation and model development to deployment, monitoring, and MLOps.
If you thrive in a fast-paced, ambiguous environment and enjoy turning complex ML systems into reliable, scalable solutions, this is a chance to influence strategy, publish technical content, and act as a trusted advisor on cloud architectures and Generative AI. (Note: if based in Montreal, bilingual French/English is required.)
About the Role
As a Senior Machine Learning Engineer in AWS Professional Services, you will lead end-to-end ML projects: understanding business needs, designing high-performance data platforms, building predictive and GenAI solutions, and implementing MLOps with AWS services (e.g., Amazon SageMaker). You’ll collaborate across DevOps, Data Engineering, IoT, and HPC to operationalize data and models at scale.
You will also mentor junior talent, develop whitepapers/blogs, and engage directly with enterprise customers to remove blockers and align solutions to industry standards. Travel to customer sites may be required.
Benefits and Salary
AWS offers a competitive total compensation package, including:
- Base salary: $126,000 – $210,400/year (based on knowledge, skills, and experience)
- Potential equity, sign-on, and other compensation elements
- Comprehensive medical, financial, and employee benefits
- Inclusive culture, mentorship, and career growth resources
Job Details
🧩 Team: AWS Professional Services (Customer-facing)
📍 Locations: Vancouver, BC • Montreal, QC • Calgary, AB • Toronto, ON
🆔 Job ID: 3062224
🏢 Company: Amazon Web Services Canada, Inc.
Requirements / Skills
- Bachelor’s degree (or equivalent experience) in a quantitative field; strong statistical foundations
- 10+ years in data/software engineering with distributed data processing and ML infrastructure
- 5+ years building platforms for predictive modeling, NLP, and deep learning
- Proficiency in SQL, Python, and one of Java/Scala/TypeScript/JavaScript
- Experience with scikit-learn, TensorFlow, PyTorch; 2+ years with cloud ML (e.g., SageMaker)
- Montreal only: Fluent French & English (bilingual requirement)
Responsibilities
- Lead end-to-end ML/AI projects (data prep → modeling → deployment → monitoring)
- Design and implement high-performance, secure data platforms
- Build scalable MLOps on AWS; leverage Generative AI where applicable
- Deliver predictive models for forecasting, resource optimization, and customer trends
- Collaborate across DevOps, Data Engineering, IoT, HPC to operationalize solutions
- Advise customers on AI/ML architectures and cloud best practices; mentor juniors
- Create technical content (whitepapers, blogs) and support standards adoption
How to Apply
Ready to help enterprises scale AI/ML on AWS? Apply on the official AWS Careers page below.
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Job Summary & Tips for Applying
For a standout application, showcase end-to-end ML ownership (from data platforms and feature engineering to deployment, monitoring, and MLOps) and your impact in customer-facing engagements. Highlight concrete results (e.g., latency reductions, cost savings, forecast accuracy), plus experience with SageMaker, pipeline automation, and governance for model lifecycle management.
Use keywords like Senior Machine Learning Engineer, MLOps on AWS, SageMaker, distributed training, GenAI/LLMs, feature stores, and end-to-end ML platforms. If you’ve published whitepapers/blogs or mentored engineers, call it out—this role values technical leadership, customer advisory, and scalable design patterns.