AI Engineer – AIOps, IT Infrastructure ML - Toronto - Astra North Infoteck Inc.

    Astra North Infoteck Inc.
    Astra North Infoteck Inc. Toronto

    3 days ago

    Description

    AI Engineer – AIOps / IT Infrastructure ML

    Role Overview

    The AI Engineer – Intelligent Operations is responsible for designing and implementing production-ready AI and machine learning (AI/ML) solutions that enhance automation, optimize processes, and provide predictive capabilities within IT infrastructure and operations. The primary focus is integrating AI into IT operations workflows and collaborating with teams specializing in observability, IT service management (ITSM), cloud, and infrastructure.



    Core Responsibilities

    AI and AIOps Engineering

    • Develop machine learning and AI models addressing key operational areas:
      • Incident prediction and early warning systems to prevent downtime.
      • Event correlation and noise reduction to streamline alerts.
      • Capacity forecasting and anomaly detection for optimal resource utilization.
    • Shift IT operations from reactive analytics to proactive, predictive operations.

    Integration with IT Operations Platforms

    • Integrate AI models with IT operations platforms, including:
      • Observability systems such as Dynatrace (logs, metrics, traces).
      • ITSM platforms, particularly ServiceNow, to improve incident and problem management workflows.
      • Automation tools to enable intelligent operational actions and remediation pipelines.

    MLOps for Infrastructure

    • Deploy models as APIs, microservices, or batch jobs to support operations teams.
    • Implement full MLOps lifecycle: model versioning, CI/CD, drift monitoring, explainability, and reliability.
    • Ensure models are production-ready, compliant, stable, and auditable, especially in banking environments.

    Cloud and Platform Engineering

    • Execute AI workloads on leading cloud platforms: Azure, AWS, GCP.
    • Optimize compute, storage, and inference costs for 24×7 operational environments.


    Required Skills

    • Proficiency in Python and machine learning engineering.
    • Expertise in time-series analysis, anomaly detection, and forecasting.
    • Hands-on experience with MLOps practices and tools.
    • Familiarity with infrastructure telemetry, including logs, metrics, and events.
    • Experience with cloud platforms and containerized environments (preferably Kubernetes).


    Preferred Attributes

    • Strong collaboration with IT operations, observability, and automation teams.
    • Experience in enterprise-scale IT infrastructure, particularly in banking or financial services.
    • Ability to translate AI/ML insights into actionable operational improvements.

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