AI Architect

7 days ago

Vancouver, British Columbia, Canada Quartech Systems Ltd Full time
About Quartech Systems Ltd

Quartech Systems Ltd is a leading provider of IT solutions and consulting services, boasting 40 years of experience in the industry. We offer tailored technology solutions, software design and development, systems integration, and comprehensive Cloud Solutions, including the MS Dynamics 365 platform.

We adhere to Agile practices and DevOps principles, ensuring we remain at the forefront of industry trends through our involvement with advanced technologies like AI and Automation, Digital Trust, and various digital and mobile applications. Our company continues to experience significant growth year after year, focusing on building highly collaborative teams who work on a range of projects across multiple industries.

Job Summary

The AI Architect will have a proven track record of providing leadership for large, complex projects in a variety of business and industry settings, with a preference for the public sector. They will embrace a team-oriented approach and prioritize customer service to ensure a positive client experience with Quartech.

Key Responsibilities
  • Design and Implement AI Solutions
    • Develop and implement AI models and systems that align with the company's strategic goals.
    • Collaborate with cross-functional teams, including data scientists, engineers, and business stakeholders, to integrate AI technologies into business processes.
  • Lead AI Projects
    • Lead the development and deployment of scalable and efficient AI solutions.
    • Monitor the performance of AI systems and continuously refine them for better efficiency and accuracy.
  • Develop AI Strategies
    • Develop AI strategies and frameworks for Quartech and clients.
    • Oversee R&D activities to develop new AI algorithms, models, and technologies.
Requirements
  • Minimum of 5 years of experience in designing and implementing machine learning models and large-scale AI solutions, and 3 years in a senior technical role.
  • Previous experience delivering projects that involve AI integration into mission-critical applications.
  • Ability to lead the creation of technical designs, models, and options for specific components of a solution by gathering functional and non-functional requirements related to compliance, performance, security, reliability, and technical aspects.
Technical Skills
  • Proven experience with machine learning and deep learning frameworks, including Keras, TensorFlow, PyTorch, and Scikit-Learn.
  • Strong background in data preprocessing, feature engineering, and data engineering practices, including ETL processes, database management, and experience with large-scale data processing frameworks, such as Apache Spark or Hadoop.
  • Previous experience with model training and fine-tuning using a variety of tools, including Hyperopt, Spearmint, and Scikit-Optimize.
  • Experience in fine-tuning and deploying commercial and open-source large language models, such as GPT, Llama, or custom models tailored to specific business needs.
  • Experience working with the NVIDIA CUDA platform.
AI and Machine Learning Experience
  • Extensive experience in designing, implementing, and evaluating both supervised and unsupervised learning models, as well as reinforcement learning, natural language processing, recommender systems, and deep learning applications.
  • Experience with securing AI models and ensuring data privacy in compliance with regulations, particularly in sensitive sectors, such as healthcare.
  • Deep understanding of AI ethics, fairness, bias mitigation, and the ability to design models that are interpretable and explainable.
Cloud and Infrastructure Knowledge
  • Experience deploying AI/ML models in production environments using cloud services, such as AWS SageMaker, Azure Machine Learning, Google AI Platform.
  • Experience with CI/CD pipelines and containerization tools, such as Docker and Kubernetes, for scalable deployment of AI models.
  • Experience with MLOps practices, including automating the end-to-end machine learning lifecycle, from model development to deployment and monitoring, using tools and frameworks, such as MLflow, Kubeflow, or TFX (TensorFlow Extended), for managing machine learning pipelines.
Soft Skills
  • Demonstrated ability to contribute to and provide leadership for complex projects with cross-functional teams.
  • Excellent problem-solving, analytical, and communication skills.
Preferred Qualifications
  • PhD or master's in computer science with a minor in Artificial Intelligence, Data Science, or a related field.
  • Experience in an AI leadership role.
  • Publications or presentations in well-known AI conferences or journals.
  • Certifications in relevant technologies, such as AWS Certified Machine Learning, Google Cloud Professional Data Engineer.
  • Knowledge of privacy and IT security policies in the public sector, including healthcare, such as FIPPA, HIPAA, SOX.

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