Machine Learning Engineer

Machine Learning Engineer

Location : Montreal CAN H8T 3H1

Duration : 12 months

Key Responsibilities

• End to End Machine Learning Development
• Build and own ML solutions from data ingestion through modelling, evaluation, deployment, and monitoring.
• Develop, train, and evaluate machine learning models using modern ML frameworks and libraries.
• Production Engineering & MLOps
• Deploy, operationalize, and maintain ML models in production environments, implementing CI/CD pipelines, Docker/containerization, orchestration, automated retraining, and monitoring.
• Write modular, production ready Python code and reusable ML components.
• Data Preparation & Feature Engineering
• Extract, clean, transform, and validate datasets from diverse sources to support robust model development.
• Handle ambiguity in real world, imperfect data and design reproducible data processing pipelines.
• Model Quality & Risk Management
• Apply rigorous evaluation practices: cross validation, bias/variance analysis, overfitting detection, and data leakage prevention.
• Monitor models for drift, performance degradation, and operational issues.
• Collaboration & Stakeholder Engagement
• Work cross functionally with engineers, developers, architects, and project teams to align technical solutions with business objectives.
• Clearly communicate findings, risks, solution design, and technical trade offs to both technical and non technical stakeholders.
• Innovation & Modern ML
• Work with emerging approaches such as LLMs, SLMs, embeddings, and prompt based workflows.
• Stay up to date with current ML engineering, MLOps practices, tooling, and cloud native capabilities.

Required Qualifications, Experience & Skills

• 5 years of experience designing and implementing end to end ML solutions in production.
• Strong command of ML algorithms, model development, training, validation, and optimization.
• Expertise in Python, ML libraries, and version control (Git).
• Clear understanding of model evaluation, data leakage, and the bias/variance trade off.
• Hands on experience with cloud platforms (AWS/Azure/GCP) and MLOps practices, including Docker, CI/CD, deployment, and monitoring.
• Demonstrated success deploying and maintaining production ML models and writing modular, production grade code.
• Strong experience preparing, transforming, and validating complex real world datasets (in Snowflake or similar cloud data platforms).
• Experience with enterprise system data (SAP, Salesforce, PLM, Teamcenter) is desirable.
• Familiarity with LLMs/SLMs and modern ML frameworks (e.g., PyTorch, TensorFlow, HuggingFace).
• Excellent problem solving abilities and communication skills.
• Proven ability to work cross functionally with engineering and product teams.

Dexian is a leading provider of staffing, IT, and workforce solutions with over 12,000 employees and 70 locations worldwide. As one of the largest IT staffing companies and the 2nd largest minority-owned staffing company in the Canada, Dexian was formed in 2023 through the merger of DISYS and Signature Consultants. Combining the best elements of its core companies, Dexian's platform connects talent, technology, and organizations to produce game-changing results that help everyone achieve their ambitions and goals.

Dexian's brands include Dexian DISYS, Dexian Signature Consultants, Dexian Government Solutions, Dexian Talent Development and Dexian IT Solutions. Visit https://dexian.com/ to learn more.

Dexian is an Equal Opportunity Employer that recruits and hires qualified candidates without regard to race, religion, sex, sexual orientation, gender identity, age, national origin, ancestry, citizenship, disability, or veteran status.

Dexian will on request provide accommodation for disabilities to support your participation in all aspects of Recruitment, Assessment and selection process.