Our client, a well-known brand, has an immediate opening for a Machine Learning Software Engineer to join their team in Toronto on a 12-month contract with the possibility of further extension.

Architect, develop, and maintain scalable cloud infrastructure using Google Cloud Platform (GCP) services such as Vertex AI, BigTable, BigQuery, and Cloud Composer.
Automate and orchestrate ML workflows, integrating data ingestion, feature engineering, training, and deployment.
Enhance platform usability and scalability, ensuring an optimized development experience for ML practitioners.
Optimize data pipelines and cloud resources for low-latency, cost-effective operations.
Implement monitoring, alerting, and failover mechanisms to ensure platform reliability and stability.
Stay at the forefront of industry trends, continuously refining best practices in cloud engineering, data engineering, and ML infrastructure.
Customer-First Mindset – Passion for building self-service ML platforms that minimize friction for data scientists.
Strong Collaboration – Ability to work closely with cross-functional teams, including Data Scientists and ML Engineers.
Problem-Solving Excellence – Analytical thinker who can identify, diagnose, and resolve technical challenges in ML pipelines, cloud infrastructure, and scalability.
Automation-First Approach – Commitment to streamlining and automating infrastructure to enhance scalability and reliability.
Adaptability & Innovation – Willingness to quickly learn new technologies and continuously improve the platform.
Ownership & Initiative – Ability to take ownership of key platform components and drive impactful improvements.
Bachelor’s or Master’s Degree in Computer Science, Engineering, or a related field.
2–5 years of experience in software engineering, with a focus on cloud infrastructure, data engineering, or ML platforms.
Hands-on experience with GCP services, including Vertex AI, BigTable, BigQuery, Cloud Composer, and Cloud Storage. Proficiency in Python, Java, or SQL for developing scalable backend solutions.
Experience with workflow orchestration tools such as Apache Airflow (Cloud Composer).
Expertise in CI/CD and DevOps tools for seamless integration and deployment.
Familiarity with containerization and orchestration (Docker, Kubernetes).
Strong analytical mindset and attention to detail.
Excellent communication skills and ability to thrive in a collaborative, fast-paced environment.

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