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Senior Machine Learning Engineer

Job in Kingston, Ontario, Canada
Listing for: Hays
Full Time position
Listed on 2026-06-11
Job specializations:
  • Engineering
    Data Engineering, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 100 - 110 CAD Hourly CAD 100.00 110.00 HOUR
Job Description & How to Apply Below

Job Title:
Machine Learning Engineer

Location:
Remote
- Canada

Duration:
Contract

Rate : CAD $100-110/hr INC

What You'll Do

  • Architect and implement advanced deep learning models for multimodal recommendation systems, processing diverse data types including text, images, user behavior, item features, offer data, and contextual signals.
  • Lead the development and optimization of generative AI applications for personalized product discovery, search enhancement, and customer engagement.
  • Expert in leveraging cutting-edge GenAI techniques, prompt engineering, transformer architectures, and own end-to-end development of scalable AI/ML pipelines
  • Design, build, and maintain highly scalable, robust, and efficient cloud infrastructure using Google Cloud Platform (GCP) services, including Vertex AI, Big Table, Big Query, Alloy

    DB, and Cloud Composer.
  • Develop automation and orchestration of ML pipelines, integrating data ingestion, feature engineering, training, and deployment processes.
  • Collaborate with cross-functional teams to understand their needs and build solutions that improve platform usability, scalability, and the overall development experience.
  • Optimize data processing pipelines and cloud resources to ensure low-latency, cost-effective operation.
  • Implement monitoring, alerting, and failover strategies to ensure platform reliability.
  • Stay updated with industry trends and best practices in cloud engineering, data engineering, and machine learning

Required Qualifications

  • Master's or PhD in Computer Science, Machine Learning, or related field.
  • 8+ years of experience in machine learning engineering, with a focus on recommendation systems or personalization.
  • Strong expertise in deep learning frameworks (PyTorch or Tensor Flow) and building production-grade ML systems.

  • Proven experience with GCP services and ML infrastructure at scale.
  • Proficient in Python, SQL, and cloud-native development.
  • Experience with containerization (Docker) and orchestration (Kubernetes).
  • Track record of deploying ML models to production at scale.

Preferred Qualifications

  • Experience with multimodal deep learning architectures and generative AI models.
  • Knowledge of modern recommendation system architectures (transformers, neural collaborative filtering).
  • Expertise in building real-time inference systems.
  • Experience with distributed computing frameworks (Spark) and big data processing.

Familiarity with Apache Airflow (Cloud Composer) and CI/CD pipelines.

Position Requirements
10+ Years work experience
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