AI/ML Development Lead

TalentBridge

  • Atlanta, GA
  • 30+ days ago

    Highlights

    We are seeking an experienced AI - Machine Learning Dev Lead to join our team, responsible for end-to-end model deployment and providing technical leadership on ML infrastructure and data engineering initiatives. The ideal candidate combines hands-on production deployment experience across the GCP ML stack with data engineering skills and a track record of leading or mentoring other engineers.

    Numbers & Facts

    LocationAtlanta, GA

    Description

    AI/ML Dev Lead

    About the Role

    We are seeking an experienced AI - Machine Learning Dev Lead to join our team, responsible for end-to-end model deployment and providing technical leadership on ML infrastructure and data engineering initiatives. This is a hands-on leadership position combining deep GCP expertise with team mentorship responsibilities.

    Required Qualifications

    • Programming: Strong practical experience with Python
    • Google Cloud Platform (GCP): Demonstrated production experience with:
      • Vertex AI
      • BigQuery
      • Cloud Run
      • Cloud Storage
    • Container Orchestration: Familiarity with GKE (Google Kubernetes Engine) / Kubernetes for deployment workflows

    Preferred Qualifications

    • End-to-end model deployment experience, including:
      • Feature engineering
      • Data transformations
      • Inference pipelines
    • Working knowledge of Vertex AI Pipelines, Kubeflow, or other cloud-native pipeline tools
    • Data engineering experience, particularly with Dataform or equivalent tools for preparing and transforming data for ML use cases

    Leadership Expectations

    • Prior experience leading a small team is strongly preferred
    • Direct report management or formal mentorship of engineers
    • This is a dev-lead position, not intended for an individual-contributor-only profile

    Ideal Candidate Profile

    The ideal candidate combines hands-on production deployment experience across the GCP ML stack with data engineering skills and a track record of leading or mentoring other engineers. Candidates with purely IC-level experience or without production model deployment history will not meet the bar for this role.
     


       

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