Machine Learning Engineer
- Toronto, ON, Canada
Contract
Applications open in a new tab.
Job details
- Job type
- Contract
- Apply by
- Posting language
- English
- Posted
Original job description
Job Title: Machine Learning Engineer - Senior
Job Location: Toronto, ON
Job Type: 130 days contract
Client: Public Sector
Job Title: Machine Learning Engineer - Senior
Description
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: Creates machine learning models and utilizes data to train models Focuses on analyzing data to find relations between the input and the desired output Understands business objectives and develops models that help achieve them, along with metrics to track their progress Designs and develops machine learning and deep learning systems Runs machine learning tests and experiments Implements appropriate machine learning algorithms General Skills: Experience managing available resources such as hardware, data, and personnel so that deadlines are met Experience analyzing the machine learning algorithms that could be used to solve a given problem and ranking them by their success probability Experience exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world Experience verifying data quality, and/or ensuring it via data cleaning Experience supervising the data acquisition process if more data is needed Experience finding available datasets online that could be used for training Experience defining validation strategies Experience defining the preprocessing or feature engineering to be done on a given dataset Background in statistics and computer programming A team player with a track record for meeting deadlines, managing competing priorities and client relationship management experience
Must Haves:
- 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. Tech stack: Python, SQL, Power BI, Power Automate, VSCode, Git, Jira, Azure (ML Studio, AI Foundry), Databricks.
- Deep understanding of ML algorithms and statistics, including classification, regression, clustering, feature engineering, model evaluation, hyperparameter tuning, drift, retraining, performance optimization and production model troubleshooting.
Location: Hybrid – 3 days a week onsite
Public Sector Experience: preferred but not required
More about this job
Responsibilities
Develop, deploy, integrate, monitor, and operationalize machine-learning solutions, establishing reusable MLOps patterns and automation to move models reliably into production. Analyze data, build and evaluate models, run experiments, and ensure solutions meet business objectives and perform effectively at scale.
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 have deep knowledge of machine-learning algorithms and statistics, including feature engineering, model evaluation, tuning, drift, retraining, and production troubleshooting.
Skills
- Python
- Azure Machine Learning
- Azure AI Foundry
- MLOps
- CI/CD
- Containerization
- API Integration
- Automation
- Model Deployment
- Model Monitoring
- Machine Learning
- Deep Learning
- Statistics
- Feature Engineering
- Model Evaluation
- Databricks
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Data & Analytics
- Engineering
- Government & Public Sector
Keywords
- Python
- SQL
- Power BI
- Power Automate
- Visual Studio Code
- Git
- Jira
- Azure Machine Learning
- Azure AI Foundry
- Databricks
- MLOps
- CI/CD
- Containers
- APIs
- Automation
- Model Deployment
- Monitoring
- Observability
- Machine Learning
- Deep Learning
- Classification
- Regression
- Clustering
- Feature Engineering
- Model Evaluation
- Hyperparameter Tuning
- Model Drift
- Model Retraining
- Performance Optimization
- Data Cleaning