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    Machine Learning Architect - Toronto, Canada - CGI

    CGI
    CGI Toronto, Canada

    4 days ago

    CGI background
    Full time
    Description

    Position Description:

    Are you a Machine Learning Architect or a Senior Data Scientist with hands-on experience with MLOps? Are you interested in working in a talented and collaborative team developing Data and AI solutions for leading global clients? If you have that technical expertise of building and productionizing ML models, a flair for leading a team of Data Scientists and ML Engineers, plus a mindset to collaborate with diverse clients and stakeholders, we're looking for you.

    This role is open to across Canada within proximity to CGI offices.

    The ET (Emerging Technologies) team in Global Technology and Operations (GTO) Canada at CGI is a trusted Data, Cloud and AI advisor and go-to implementation partner for our global clients' Data and Advanced Analytics needs. We're an entrepreneurial team that is on a continuous mission to position CGI as the best-in-class AI partner and develop new and exciting opportunities in latest technologies including Generative AI. In our endeavor to provide end-to-end AI capabilities, we start with learning about the clients` business and data landscape, assess possible opportunities, help shortlist and turn those opportunities into action, and then scale it across the organization unlocking a larger impact for clients and their consumers. For this, we depend on a talented and motivated team of Data Architects, Data Scientists, Data Engineers, Cloud DevOps professionals, Cloud Architects and other solutions experts.

    Your future duties and responsibilities:

    As a hands-on Machine Learning Architect on the team your responsibilities will include:
    - strategically collaborating with the client stakeholders and account teams to explore and implement key AI solutions
    - keeping a holistic architectural mindset when designing and implementing AI architecture for clients - ML implementation, Data Engineering, MLOps, Data Privacy and Responsible AI, Data Governance
    - leading a team of multiple Data Scientists and Data Engineers in a client engagement setting
    - Also being "hands-on" to build, tune, deploy and monitor robust Machine Learning models and components in on-premise or cloud environments
    - Gathering client requirements, coding and implementing reusable data pipelines to support ML modelling
    - Implementing proof of concepts to show value and then package and scale to full ML models at scale on both on-prem and cloud environments
    - Supporting the other Data Scientists in the team with technical knowledge and mentorship

    Required qualifications to be successful in this role:

    Essential Qualifications
    - 5 years or more "hands-on" working experience delivering diverse Advanced Analytics solutions
    - Some experience leading small or big technical teams implementing ML solutions in any industry
    - Hands-on expertise in building and deploying code using Python, Pyspark, SQL and major programming languages with at least one major Cloud platform (Azure, AWS, or GCP)
    - Excellent communication and mentorship skills

    Desired qualifications
    - Data Governance and Data Mesh/Data Fabric implementation experience
    - Experience leading technical teams of Data Scientists
    - Experience with large datasets on cloud and experience with Hadoop and HDFS
    - End-to-end ML experience including MLOps experience
    - Experience with Google Vertex AI, AWS Sagemaker or Azure Cognitive Services
    - Experience with Generative AI projects is an asset

    Skills:

  • Advanced Analytics
  • Artificial Intelligence
  • Google Cloud Platform
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