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GCP AI/ML Engineer

CanadaOnsiteContractPosted 2 months ago

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Role summary

This role is for a GCP AI/ML Engineer responsible for developing AI/ML strategies and architectures on Google Cloud. The engineer will lead the design and deployment of scalable AI solutions, including Generative AI and computer vision models, utilizing GCP services like Vertex AI, Gemini, and BigQuery ML. Key responsibilities include ensuring production-grade performance, security, and adherence to MLOps best practices. The role requires expert-level Python programming, deep understanding of AI frameworks, and proven experience leading technical teams. Familiarity with Docker, Kubernetes, and CI/CD is also essential.

Responsibilities

  • Develop AI/ML strategies, defining architecture and best practices for developing and deploying AI systems on Google Cloud.
  • Lead the design of scalable production-grade AI solutions, including Generative AI, multi-agent orchestration, and computer vision models on Vertex AI.
  • Use Google Cloud's AI suite, including Vertex AI, Gemini models, BigQuery ML, Dataflow, and TPU/GPU hardware for training and inference.
  • Guide team members on Python, TensorFlow/PyTorch, API integrations, and CI/CD pipelines.
  • Ensure scalability, security, and performance of AI/ML models in production, adhering to MLOps best practices.
  • Partner with business units and external clients to translate requirements into technical solutions.

Required Qualifications

  • Bachelor’s or Master's degree in Computer Science, AI, or a related technical field.
  • 6+ years of experience with cloud platforms, with strong emphasis on Google Cloud Platform and its AI/ML services.
  • Deep understanding of AI frameworks (TensorFlow, PyTorch, Scikit-learn), neural network architectures, and agentic workflows.
  • Expert-level Python programming, including experience with Data Science libraries.
  • Proven experience leading technical teams, setting team priorities, and driving complex projects from development into production.
  • Familiarity with Docker, Kubernetes (GKE), and CI/CD tools.

Preferred Qualifications

  • Professional Machine Learning Engineer Certification (Google Cloud).
  • Experience building and deploying large-scale infrastructure and distributed systems.
  • Experience in AI application in sectors such as Financial Services, Healthcare, or High-Tech (Semiconductors).
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