Our client located in Downtown Toronto is hiring a Machine Learning Engineer. As a public sector organization, the successful candidate will be required to be in office 5x per week as of January 2026.

Core Requirements

1. Solid Machine Learning Engineering Skills (Standard, Not Exotic)

The successful candidate will have expertise in:

• Machine learning concepts
• Deep learning frameworks
• Data processing
• Feature engineering
• Optimization techniques
• Model training & deployment principles

Not a research-heavy role more practical ML engineering.

2. Strong Communication

They need someone who can explain ML concepts clearly and discuss problem-solving approaches during interviews.

3. Up-to-Date Knowledge

They want someone who stays current on ML trends, frameworks, and best practices.

4. Ability to Perform in Interview

This is crucial.

The successful candidate must:

• Answer practical ML questions
• Explain architecture/design choices
• Demonstrate depth, not just buzzwords

This role heavily relies on interview performance and the candidate’s ability to articulate their ML knowledge.

Our client is focused on skills, communication, and technical depth,

Key Technical Areas for the successful candidate

Machine Learning Skills

• Classical ML (regression, classification, clustering)
• Experience tuning models
• Understanding of bias/variance
• Evaluation metrics

Deep Learning

• Experience with frameworks like:
• TensorFlow
• PyTorch
• Keras

Data Engineering / Pipeline Skills

• Data cleaning
• Feature engineering
• Model pipelines
• Understanding of data scalability

Optimization

• Hyperparameter tuning
• Performance improvements
• Model deployment considerations