Machine Learning Jobs in Irving, TX

The Associate Manager will lead DLP operations, manage a technical team, support security risk reduction, and optimize DLP processes in collaboration with stakeholders.

The role involves leading AI automation product teams, guiding development, overseeing strategic initiatives, and driving collaboration for operational excellence.

The role involves analyzing conversational data, enhancing NLP accuracy, monitoring AI model performance, and leading AI initiatives in a contact center environment.

The Data & Operations Analyst role focuses on solving operational problems, developing actionable insights, utilizing Python and SQL for analysis, and collaborating with cross-functional teams.

The Vice President Consumer Marketing will develop commercialization strategies, manage product roadmaps, and lead teams to enhance early detection cancer products while ensuring regulatory compliance and market growth.

The role leads application systems analysis and programming, drives architecture strategy, evaluates technologies, and influences senior stakeholders in the investment domain.

You will develop innovative data science solutions, including LLM-based agents and predictive models using machine learning on complex datasets.

The Lead AI Engineer will manage AI/ML model production, ensure deployment pipelines, mentor teams, and enhance AI systems with innovative technologies.

The MLOps Engineer will operationalize and scale AI/ML applications, manage CI/CD pipelines, develop ML pipelines, and collaborate closely with data scientists and ML engineers.

The Senior Software Engineer will lead data engineering initiatives, design scalable web services, and mentor teammates while ensuring technical alignment with business goals.

The AI & ML Platform Engineer, VP designs AI & ML platform solutions, implements hybrid cloud architectures, and drives strategy for data analytics at Citi.

Design, develop, and deploy AI-driven applications using Generative AI and LLMs. Manage projects from conception to deployment and ensure compliance with regulations.

Validate ML and generative AI healthcare solutions across the development lifecycle. Design and run automated, data-driven test strategies, LLM evaluation and prompt regression suites, monitor drift and safety, build dashboards and alerting, and partner with cross-functional teams to define quality gates and remediate defects.

Lead design and implementation of machine learning and modeling initiatives. Oversee teams, ensure model governance, and drive data-informed decision making.