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Durham, NC, USA
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Job Responsibilities include:
Define, design, and implement enterprise AI/ML solution architectures aligned with business goals and digital transformation initiatives.
Lead end-to-end AI solution delivery, including data ingestion, model development, validation, deployment, monitoring, and optimization.
Design scalable AI/ML pipelines leveraging cloud platforms such as AWS, Azure, and GCP, while ensuring performance, reliability, and security.
Collaborate with business stakeholders, data scientists, engineers, and developers to translate business requirements into innovative AI-driven solutions.
Establish and promote MLOps best practices, including CI/CD pipelines, model lifecycle management, version control, monitoring, and retraining strategies.
Evaluate emerging AI technologies, mitigate risks related to model bias, drift, and compliance, and provide technical leadership and mentorship across cross-functional teams.
Required Qualifications:
Bachelor’s or master’s degree in computer science, Artificial Intelligence, Data Science, Machine Learning, Engineering, Information Technology, or a related field.
10+ years of experience in software, data, or AI/ML solution architecture, with proven experience delivering enterprise-scale AI initiatives.
Strong expertise in AI/ML technologies, including Machine Learning, Deep Learning, NLP, Generative AI, TensorFlow, PyTorch, Scikit-learn, and programming languages such as Python, R, or Java.
Hands-on experience designing and deploying end-to-end AI solutions on AWS, Azure, or Google Cloud, with strong knowledge of MLOps, model lifecycle management, data engineering, cloud architecture, and enterprise system integration
Any Graduate
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