Machine Learning Engineer

Montreal, QC (Hybrid, 2–3 days onsite per week)

Language

English, advanced written and verbal communication required. French is considered an asset.

Duration

12-Month Contract

About the Opportunity

We are seeking an experienced Machine Learning Developer to join a leading organization focused on leveraging advanced technology and data-driven insights to solve complex business challenges. This opportunity is ideal for someone who enjoys building intelligent systems from the ground up and delivering machine learning solutions that create measurable impact across a large-scale digital ecosystem.

Working alongside data engineers, software developers, product leaders, and business stakeholders, you will transform real-world data into scalable production‑ready solutions. This role combines machine learning, MLOps, and software engineering, offering the opportunity to influence both technical direction and business outcomes.

What’s In It for You

Exposure to complex, enterprise‑scale machine learning initiatives

Opportunities to work with modern ML frameworks, cloud technologies, and emerging AI solutions

A collaborative environment that values innovation, continuous learning, and knowledge sharing

Meaningful work that directly supports business‑critical decision making

Flexibility through a hybrid work model and a team‑oriented culture

Your Responsibilities

You’ll design, develop, deploy, and maintain end-to-end machine learning solutions from data ingestion through production monitoring

You’ll build, train, evaluate, and optimize machine learning models using modern frameworks and best practices

You’ll develop scalable data pipelines and feature engineering processes to support reliable model performance

You’ll implement MLOps practices including CI/CD pipelines, containerization, deployment automation, and monitoring

You’ll identify and mitigate risks related to model drift, data quality, overfitting, and data leakage

You’ll collaborate with cross‑functional teams to translate business requirements into practical ML solutions

Skills and Qualifications

5+ years of experience designing and implementing end-to-end machine learning solutions in production environments

Strong expertise in Python, Git, and machine learning libraries such as PyTorch, TensorFlow, or Hugging Face

Proven experience with model development, training, validation, optimization, and evaluation methodologies

Hands‑on experience with cloud platforms such as AWS, Azure, or GCP

Strong knowledge of MLOps practices including Docker, CI/CD, deployment, monitoring, and automated retraining

Experience working with Snowflake or similar cloud‑based data platforms and complex real‑world datasets

Excellent communication, problem‑solving, and stakeholder collaboration skills

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