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MLOps Engineer

3 weeks ago

Greater Toronto Area, Canada Hays Full time

Your New Company

You will be joining a major, forward‑thinking organization that is investing heavily in scalable machine learning platforms and cloud‑native infrastructure. The team is focused on enabling frictionless experimentation, deployment, and production operations for Data Scientists and ML Engineers across the enterprise.

Your New Role

As an
MLOps Engineer
, you will architect and maintain robust, scalable cloud infrastructure using Google Cloud Platform. You will play a key role in automating end‑to‑end ML workflows, optimizing data pipelines, and ensuring the reliability, performance, and usability of the ML platform.

  • Architecting, developing, and maintaining scalable cloud infrastructure using
    Vertex AI, BigTable, BigQuery, Cloud Composer, and Cloud Storage
    .
  • Automating and orchestrating ML workflows, integrating data ingestion, feature engineering, model training, and deployment.
  • Enhancing platform usability and scalability to ensure a seamless experience for ML practitioners.
  • Optimizing data pipelines and cloud resources for
    low‑latency
    and
    cost‑efficient
    performance.
  • Implementing monitoring, alerting, observability, and failover mechanisms to ensure platform reliability and stability.
  • Staying up to date on industry trends and continuously refining best practices in cloud engineering, data engineering, and ML infrastructure.

What You'll Need to Succeed

  • A
    customer‑first mindset
    with a passion for building self‑service ML platforms.
  • Strong collaboration skills with the ability to partner closely with Data Scientists and ML Engineers.
  • Excellent analytical and problem‑solving abilities to diagnose issues in ML pipelines and cloud infrastructure.
  • An
    automation‑first approach
    , focused on building scalable, reliable, repeatable systems.
  • Adaptability with a willingness to learn new technologies and continuously enhance the platform.
  • Strong ownership mentality and the ability to drive meaningful improvements.
  • Bachelor's or Master's degree in Computer Science, Engineering, or related fields.
  • 5+ years of software engineering experience
    , focused on cloud infrastructure, data engineering, or ML platforms.
  • Hands‑on experience with
    GCP
    services including Vertex AI, BigTable, BigQuery, Cloud Composer, and Cloud Storage.
  • Proficiency in
    Python, Java, or SQL
    for building scalable backend and data solutions.
  • Experience with
    Apache Airflow / Cloud Composer
    .
  • Strong knowledge of
    CI/CD
    , DevOps tools, and automation frameworks.
  • Familiarity with
    Docker
    and
    Kubernetes
    .
  • Excellent communication skills and the ability to thrive in a fast‑paced, collaborative environment.

What You'll Get in Return

  • The opportunity to influence large‑scale ML platform architecture and core infrastructure.
  • A collaborative, innovation‑focused environment with strong engineering culture.
  • Competitive compensation, benefits, and professional growth opportunities.
  • Exposure to leading cloud technologies and enterprise‑level ML operations.

What You Need to Do Now

If you're interested in exploring this opportunity, feel free to send over your updated resume or let me know when you'd like to connect to discuss next steps.