AI/ML Development Lead

We are seeking an experienced AI - Machine LearningDev 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

• 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
• 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.

AI/ML Dev Lead

About the Role

We are seeking an experienced AI - Machine LearningDev 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.

“ TalentBridge employees are eligible for many benefit offerings such as medical, dental, vision, life insurance, short term disability, 401(k) and holiday pay!”

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