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Mid-level metro role with broad ML/MLOps requirements increases applicant competition.
Strong ML/MLOps technical demands and banking preference limit cross-industry transferability.
Multiple explicit experience, technical, and managerial requirements enforce strict candidate filtering.
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Lead and mentor a team of AI/ML professionals to develop and deploy scalable machine learning models.
Define and execute AI/ML strategy aligned with organizational goals, managing project lifecycles from R&D to deployment.
Collaborate with cross-functional teams to integrate AI/ML solutions into products, ensuring model quality, performance, and explainability.
3+ years hands-on experience in machine learning, deep learning, or data science.
2+ years experience leading or managing technical teams.
Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or related field.
Proficiency in Python, R, or Java; experience with MLOps, model deployment, and cloud platforms (AWS, GCP, or Azure).
Experienced in managing AI/ML teams and projects end-to-end with strategic and operational accountability.
Technically strong with knowledge of distributed systems (Apache Kafka, Ignite, Spark), GPU infrastructure, and containerization (Docker, Kubernetes).
Experienced in deploying production-grade ML solutions with CI/CD pipelines and possibly domain experience in Banking.