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Metro mid-level role with niche GCP/ML requirements, so applicant density is moderate.
Core AI/ML and GCP skills are broadly transferable; payments experience is only advantageous, not mandatory.
Explicit 5+ years, required GCP ML experience and MLOps skills create stringent technical filters.
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Architect and design AI/ML solutions leveraging Google Cloud Platform (GCP) services such as Vertex AI, BigQuery, Dataflow, and Cloud Functions.
Lead end-to-end AI project lifecycle including requirements gathering, prototyping, development, deployment, and monitoring on GCP.
Develop scalable data pipelines and optimize AI workloads for performance, cost, and reliability while advising on data governance and security.
Bachelor's or Master's degree in Computer Science, Engineering, or related field.
5+ years of AI/ML solution architecture experience with at least 2 years working on GCP.
Hands-on experience with GCP AI/ML services (Vertex AI, BigQuery ML, AutoML) and strong knowledge of data engineering on GCP.
Proficiency in Python and SQL; familiarity with TensorFlow, PyTorch, or scikit-learn is a plus.
Experienced in end-to-end AI/ML solution delivery on GCP with technical leadership and mentorship capabilities.
Strong knowledge of MLOps, CI/CD pipelines, and model deployment specifically on GCP with awareness of security, IAM, and cost management.
Comfortable collaborating across teams to translate business requirements into scalable technical solutions, preferably with expertise in regulated industries or multi-cloud AI architectures.