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Added 1 day ago
SM
RQ00245 – Machine Learning Engineer – Senior
S M Software Solutions Inc
Toronto, ON
- Full-time
Work Arrangement: Hybrid – 3 Days per Week Onsite · Onsite Requirement: 3 days per week onsite
Added 1 day ago
SM
RQ00244 – Data Science Developer – Senior
S M Software Solutions Inc
Toronto, ON
- Internship
Work Arrangement: Hybrid – 3 Days per Week Onsite · Onsite Requirement: 3 days per week at the client's Toronto office
Added 1 day ago
SM
RQ00244 – Data Science Developer – Senior
S M Software Solutions Inc
Toronto, ON
- Internship
Work Arrangement: Hybrid – 3 Days per Week Onsite · Onsite Requirement: 3 days per week at the client's Toronto office
Added 1 day ago
SM
RQ00241 – Software Developer – ETL – Senior
S M Software Solutions Inc
Toronto, ON
- Internship
Work Arrangement: Hybrid – 3 Days per Week Onsite
Added 1 day ago
SM
RQ00241 – Software Developer – ETL – Senior
S M Software Solutions Inc
Toronto, ON
- Internship
Work Arrangement: Hybrid – 3 Days per Week Onsite
Added 1 day ago
FT
Machine Learning Engineer
FDE Times
Toronto, ON · Greater Toronto Area, Canada
- Full-time
Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals
Added 1 day ago
FT
Senior Machine Learning Engineer
FDE Times
Toronto, ON · Greater Toronto Area, Canada
- Full-time
Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals
Added 1 day ago
FT
Full Stack LLM Engineer
FDE Times
Toronto, ON
- Full-time
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750…
Added 1 day ago
FT
Applied Machine Learning Research Scientist
FDE Times
Toronto, ON
- Full-time
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750…
Added 1 day ago
A
Principal, AI Agent Control & Governance
ATB
Edmonton, AB · Calgary, AB
- Full-time
…velocity is maximized while maintaining audit-ready alignment with OSFI regulatory expectations (Guideline E-23 Model Risk Management, E-21 Operational Risk), enterprise risk appetites, and…
Added 2 days ago
SM
RQ00241 – Software Developer – ETL – Senior
S M Software Solutions Inc
Toronto, ON
- Internship
Work Arrangement: Hybrid – 3 Days per Week Onsite
Added 2 days ago
SM
RQ00244 – Data Science Developer – Senior
S M Software Solutions Inc
Toronto, ON
- Internship
Work Arrangement: Hybrid – 3 Days per Week Onsite · Onsite Requirement: 3 days per week at the client's Toronto office
Added 2 days ago
SM
RQ00244 – Data Science Developer – Senior
S M Software Solutions Inc
Toronto, ON
- Internship
Work Arrangement: Hybrid – 3 Days per Week Onsite · Onsite Requirement: 3 days per week at the client's Toronto office
Added 2 days ago
SM
RQ00245 – Machine Learning Engineer – Senior
S M Software Solutions Inc
Toronto, ON
- Full-time
Work Arrangement: Hybrid – 3 Days per Week Onsite · Onsite Requirement: 3 days per week onsite
Added 2 days ago
SM
RQ00244 – Data Science Developer – Senior
S M Software Solutions Inc
Toronto, ON
- Internship
Work Arrangement: Hybrid – 3 Days per Week Onsite · Onsite Requirement: 3 days per week at the client's Toronto office
Added 2 days ago
SM
RQ00245 – Machine Learning Engineer – Senior
S M Software Solutions Inc
Toronto, ON
- Full-time
Work Arrangement: Hybrid – 3 Days per Week Onsite · Onsite Requirement: 3 days per week onsite
Added 2 days ago
SM
RQ00241 – Software Developer – ETL – Senior
S M Software Solutions Inc
Toronto, ON
- Internship
Work Arrangement: Hybrid – 3 Days per Week Onsite
Added 2 days ago
SM
RQ00245 – Machine Learning Engineer – Senior
S M Software Solutions Inc
Toronto, ON
- Full-time
Work Arrangement: Hybrid – 3 Days per Week Onsite · Onsite Requirement: 3 days per week onsite
Added 2 days ago
SM
RQ00241 – Software Developer – ETL – Senior
S M Software Solutions Inc
Toronto, ON
- Internship
Work Arrangement: Hybrid – 3 Days per Week Onsite
Added 2 days ago
SM
RQ00245 – Machine Learning Engineer – Senior
S M Software Solutions Inc
Toronto, ON
- Full-time
Work Arrangement: Hybrid – 3 Days per Week Onsite · Onsite Requirement: 3 days per week onsite
Added 2 days ago
SM
RQ00244 – Data Science Developer – Senior
S M Software Solutions Inc
Toronto, ON
- Internship
Work Arrangement: Hybrid – 3 Days per Week Onsite · Onsite Requirement: 3 days per week at the client's Toronto office
Added 2 days ago
SM
RQ00241 – Software Developer – ETL – Senior
S M Software Solutions Inc
Toronto, ON
- Internship
Work Arrangement: Hybrid – 3 Days per Week Onsite
Added 2 days ago
FT
AI Field Engineer, EMEA
FDE Times
London, ON
- Full-time
Strong Python skills. Comfortable reading, writing, and debugging production code. Familiarity with Kubernetes and infrastructure engineering.
Added 3 days ago
RB
Senior Manager, AI Engineering (AML &Fraud)
Royal Bank of Canada
Vancouver, BC
- Full-time
Must have a strong technical background, with practical experience supporting integration testing, and development with one or more language (.Net, Java, Python)
Added 3 days ago
RB
Lead, Full Stack Engineer
Royal Bank of Canada
Vancouver, BC
- Full-time
Software engineering background with at least one of the following languages: .NET, Java, or Python

S M Software Solutions Inc

RQ00245 – Machine Learning Engineer – Senior

Toronto, ON, Canada

Hybrid

Full-time

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Job details

Job type: Full-time
Workplace: Hybrid
Apply by: Dec 8, 2026
Posting language: English
Posted: Nov 8, 2026

Original job description

Client: Metrolinx – RQ00245

We are seeking a highly skilled Senior Machine Learning Engineer with advanced hands-on experience in Azure Machine Learning, Microsoft Foundry/Azure AI Foundry, Machine Learning Operations (MLOps), CI/CD, containers, APIs, automation, model deployment, monitoring, and observability. The ideal candidate will have strong Python and machine-learning engineering expertise, with a proven ability to take machine-learning models from experimentation through development and into reliable production environments. The successful candidate will design, develop, deploy, integrate, monitor, and operationalize AI and machine-learning solutions using modern MLOps practices, establishing reusable deployment patterns, tools, monitoring, and automation to support enterprise-scale AI solutions.

Role Snapshot

Job Title: RQ00245 – Machine Learning Engineer – Senior
Client: Metrolinx
Work Location: 277 Front Street West, Toronto, Ontario, Canada
Work Arrangement: Hybrid – 3 Days per Week Onsite
Estimated Start Date: November 23, 2026
Estimated End Date: May 23, 2027
Business Days: 130.00
Hours: 7.25 hours per day
Public Sector Experience: Preferred but not required

Must Have

Advanced hands-on experience with Azure Machine Learning, Microsoft Foundry/Azure AI Foundry, MLOps, CI/CD, containers, APIs, automation, model deployment, monitoring, and observability.
Strong Python and machine-learning engineering skills, with demonstrated experience taking models from experimentation into reliable production environments.
Experience with the following technology stack:
- Python
- SQL
- Power BI
- Power Automate
- Visual Studio Code (VS Code)
- Git
- Jira
- Azure (ML Studio, AI Foundry)
- Databricks
Deep understanding of machine-learning algorithms and statistics, including:
- Classification
- Regression
- Clustering
- Feature Engineering
- Model Evaluation
- Hyperparameter Tuning
- Model Drift
- Model Retraining
- Performance Optimization
- Production Model Troubleshooting

Description

Senior Machine Learning Engineer

The Senior Machine Learning Engineer will deploy, integrate, monitor, and operationalize AI and machine-learning solutions using modern MLOps practices. The role will establish reusable deployment patterns, tooling, monitoring, and automation that enable AI solutions to move reliably from development into production and scale across the enterprise.

Responsibilities

Deploy, integrate, monitor, and operationalize AI and machine-learning solutions using modern MLOps practices.
Establish reusable deployment patterns, tooling, monitoring, and automation.
Enable AI solutions to move reliably from development into production and scale across the enterprise.
Create machine-learning models and utilize data to train models.
Focus on analysing data to find relationships between the input and the desired output.
Understand business objectives and develop models that help achieve them, along with metrics to track their progress.
Design and develop machine-learning and deep-learning systems.
Run machine-learning tests and experiments.
Implement appropriate machine-learning algorithms.

General Skills

Experience managing available resources such as hardware, data, and personnel to ensure deadlines are met.
Experience analysing machine-learning algorithms that could be used to solve a given problem and ranking them by their probability of success.
Experience exploring and visualizing data to gain an understanding of it, and then identifying differences in data distribution that could affect performance when deploying the model in real-world environments.
Experience verifying data quality and/or ensuring data quality through data cleaning.
Experience supervising the data acquisition process when additional data is required.
Experience finding available datasets online that could be used for training.
Experience defining validation strategies.
Experience defining the preprocessing or feature engineering to be performed on a given dataset.
Background in statistics and computer programming.
A team player with a track record of meeting deadlines, managing competing priorities, and demonstrating client relationship management experience.

Additional Information

Work Location: 277 Front Street West, Toronto, Ontario, Canada.
Work Arrangement: Hybrid.
Onsite Requirement: 3 days per week onsite.
Public Sector Experience: Preferred but not required.
Contract Duration: November 23, 2026, to May 23, 2027.
Working Hours: 7.25 hours per day.

How to Apply

If you are interested and your profile matches the requirements, kindly submit the following mandatory documents to hrsmss@smsoftconsulting.com by Monday, November 9, 2026, at 8:00 AM EST.

Mandatory Documents

Updated Resume in Word format (Mandatory)
Skills Matrix and References (Mandatory)
Expected Hourly Rate (Mandatory)
Visa Status (Mandatory)
LinkedIn ID (Mandatory)

Please note that we cannot proceed with your submission without the following mandatory documents.

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You have received this message either as a result of contacting our company to express interest in employment or as a result of posting your resume in a location that can be accessed by recruiters or HR specialists, which suggests an interest in being contacted about employment opportunities.

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More about this job

Responsibilities

Design, develop, deploy, integrate, monitor, and operationalize machine-learning and AI solutions using modern MLOps practices. Establish reusable deployment patterns, tooling, monitoring, and automation to move models reliably into production and support enterprise-scale solutions.

Requirements

Requires advanced hands-on experience with Azure Machine Learning or Azure AI Foundry, MLOps, CI/CD, containers, APIs, automation, deployment, monitoring, and observability, along with strong Python and machine-learning engineering skills. Candidates should understand machine-learning algorithms and statistics, and have experience with data preparation, feature engineering, validation, model evaluation, and production troubleshooting.

Skills

Azure Machine Learning
Azure AI Foundry
MLOps
Python
Machine Learning Engineering
CI/CD
Containerization
API Integration
Model Deployment
Model Monitoring
Observability
SQL
Databricks
Feature Engineering
Model Evaluation
Statistics

Visa sponsorship

Not detected in the job text

Keywords

Azure Machine Learning
Microsoft Foundry
Azure AI Foundry
MLOps
CI/CD
Python
SQL
Power BI
Power Automate
Visual Studio Code
Git
Jira
Databricks
Machine Learning
Deep Learning
Classification
Regression
Clustering
Feature Engineering
Model Evaluation
Hyperparameter Tuning
Model Drift
Model Retraining
Model Deployment
Model Monitoring
Observability
Containers
APIs
Data Cleaning
Data Visualization

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Work requirements

Jobs in Canada