Machine Learning Jobs in Irving, TX

Lead end-to-end data architecture and analytics for Parts Sales to End Users (STU): design Snowflake data models, build scalable data pipelines, develop Power BI dashboards, support forecasting and ML models, validate data quality, drive automation and system modernization, and communicate insights to senior stakeholders to improve reporting, forecasting, and business decisions.

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

As a Data Scientist in the Innovation Team, you'll develop machine learning algorithms on molecular sequencing data to enhance cancer diagnostics and treatment, collaborating with diverse experts on high-impact projects.

The Cybersecurity AI_ML Engineer develops and maintains security systems using AI and machine learning, implements threat detection, analyzes security metrics, and collaborates on security incidents.

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

The Global Financial Crimes Analyst evaluates and implements technologies to enhance compliance and risk detection in financial crimes. Responsibilities include collaborating with functional teams, developing automation solutions, analyzing vendors, and supporting compliance initiatives.

Lead a team of product managers in shaping technology products, collaborate with data scientists and engineers, and prioritize product opportunities based on client needs and business goals.

The role focuses on developing advanced React-based user interfaces for Credit Risk applications, integrating AI innovations, and collaborating with cross-functional teams to enhance user experience and performance.

Lead the design and implementation of AI/ML systems, focusing on Generative AI and Agentic AI, while collaborating with teams to drive innovation and optimize engineering processes.

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.

Design, build, and deploy scalable AI and machine learning solutions, leading full AI lifecycle, collaborating with teams, and ensuring systems align with client needs.

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