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Tier-1 employer plus metro location but senior specialized role reduces generic applicant density.
Requires deep ML, data engineering, cloud, and financial services experience limiting cross-industry transferability.
Explicit 10+ years, VP level, and many mandatory ML, data, cloud and deployment skills make filters strict.
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Lead design and development of AI/ML solutions utilizing microservices, RESTful APIs, and distributed architectures.
Develop and optimize foundational and fine-tuned machine learning models using tools like PyTorch, TensorFlow, and generative AI frameworks.
Oversee data engineering pipelines, cloud-native architecture deployment on AWS/Azure/GCP, and implement enterprise-scale Agile delivery following the SAFe framework.
10+ years of experience in microservices, AI/ML development, and distributed systems.
Proficiency in Python, Java, FastAPI, AI/ML frameworks (PyTorch, TensorFlow), and cloud platforms (AWS, Azure, GCP).
Experience working in large-scale financial services enterprise environments.
Strong knowledge of SAFe Agile methodology, DevOps, CI/CD, container orchestration, and observability tools.
Experienced leader in enterprise-scale AI/ML system design with strong stakeholder and executive communication skills.
Demonstrates deep expertise in integrating generative AI with data engineering and production deployment.
Comfortable in complex financial services settings leveraging cloud-native, Agile, and DevOps practices.