Machine Learning Engineer
Hays
Role: Machine Learning Engineer - Contract
Length: 1 year (potential for extension)
Location: Calgary (Hybrid, 2 days onsite)
Your New Company
Join 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 Role
As 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 roadmaps
- Building and optimizing machine learning models and supporting data pipelines
- Providing software development expertise to data science and analytics teams
- Translating business requirements into technical solutions and estimating implementation effort
- Prototyping and experimenting with new ML solutions
- Collaborating cross-functionally with architects, product teams, and business stakeholders
- Designing and implementing model deployment strategies (automation, monitoring, drift detection)
- Applying software engineering best practices (CI/CD, testing, maintainability) to ML solutions
- Testing, debugging, and improving application code
- Conducting code reviews and contributing to engineering excellence across the team
What You’ll Need to Succeed
Must-Have Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field
- 3+ years of hands-on experience delivering AI/ML solutions in production environments
- 2+ years of experience as a software developer within a delivery-focused team
- Strong 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 AWS
- Solid understanding of both relational and non-relational databases (SQL and NoSQL)
- Strong foundation in statistical concepts and applying data-driven problem solving
- Experience with DevOps practices, automation, and deployment pipelines
- Deep understanding of machine learning algorithms, techniques, and agentic/AI-driven solutions
- Strong testing, debugging, and troubleshooting capabilities
- Excellent collaboration and communication skills in a team environment
Nice-to-Have:
- Experience building scalable data pipelines
- Exposure to frontend/web application development
- Hands-on experience within the AWS ecosystem
- Experience working with platforms such as Databricks
What You’ll Get in Return
- Opportunity to work on cutting-edge AI/ML and data products at enterprise scale
- Exposure to modern cloud ecosystems and advanced ML deployment practices
- Collaborative, high-performing engineering and data teams
- Competitive compensation and long-term contract opportunity
- Flexible hybrid working environment
What You Need to Do Now
If 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.
Vacancy posted 11 days ago
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