Machine Learning Engineer

Role: Machine Learning Engineer - ContractLength: 1 year (potential for extension)Location: Calgary (Hybrid, 2 days onsite)Your New CompanyJoin a leading enterprise organization undergoing a major transformation in its data and AI capabilities. You’ll be part of a high-performing, collaborative team focused on building scalable machine learning solutions that drive meaningful business impact across the organization.

Your New RoleAs a Machine Learning Engineer, you will operate at the intersection of software engineering and advanced machine learning—owning the design, development, and optimization of ML models and data-driven applications.

Key responsibilities include

Participating in team planning sessions and contributing to delivery roadmapsBuilding and optimizing machine learning models and supporting data pipelinesProviding software development expertise to data science and analytics teamsTranslating business requirements into technical solutions and estimating implementation effortPrototyping and experimenting with new ML solutionsCollaborating cross-functionally with architects, product teams, and business stakeholdersDesigning and implementing model deployment strategies (automation, monitoring, drift detection)Applying software engineering best practices (CI/CD, testing, maintainability) to ML solutionsTesting, debugging, and improving application codeConducting code reviews and contributing to engineering excellence across the teamWhat You’ll Need to SucceedMust-Have Qualifications:

Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field3+ years of hands-on experience delivering AI/ML solutions in production environments2+ years of experience as a software developer within a delivery-focused teamStrong software engineering fundamentals (TDD, CI/CD, version control, etc.)Proficiency in at least two programming languages (e.g., Python, Java, C#)Hands-on experience with Python data libraries and building solutions in AWSSolid understanding of both relational and non-relational databases (SQL and NoSQL)Strong foundation in statistical concepts and applying data-driven problem solvingExperience with DevOps practices, automation, and deployment pipelinesDeep understanding of machine learning algorithms, techniques, and agentic/AI-driven solutionsStrong testing, debugging, and troubleshooting capabilitiesExcellent collaboration and communication skills in a team environmentNice-to-Have:

Experience building scalable data pipelinesExposure to frontend/web application developmentHands-on experience within the AWS ecosystemExperience working with platforms such as DatabricksWhat You’ll Get in ReturnOpportunity to work on cutting-edge AI/ML and data products at enterprise scaleExposure to modern cloud ecosystems and advanced ML deployment practicesCollaborative, high-performing engineering and data teamsCompetitive compensation and long-term contract opportunityFlexible hybrid working environmentWhat You Need to Do NowIf you’re a Data Scientist who thrives in a hands-on, engineering-focused ML environment, apply now or reach out directly for a confidential discussion.