Top Hybrid Machine Learning Engineer Jobs in Dallas-Fort Worth, TX

Lead development and evaluation of statistical and machine learning models to assess credit risk and challenge production models. Use Python, cloud, and big-data tools to analyze large numeric and textual datasets, partner with cross-functional credit risk and product teams, translate technical findings into business actions, and drive model validation, backtesting, and innovation.

The role involves designing and implementing AI and machine learning solutions, transforming data into insights, and supporting client engagements. Responsibilities include model development, data analysis, and enhancing model performance using established technologies.

Lead the architecture and platform for an enterprise Internal Analytics & AI web gateway on Azure. Own end-to-end application, data, and platform design; drive CI/CD, containerization, observability, security, and onboarding of domain apps. Build reusable AI semantic layers, transition BI workloads to AI-first experiences, and lead a platform team while coordinating governance, compliance, and stakeholder alignment.

The Senior Machine Learning Engineer will develop and optimize ML infrastructure, create data pipelines, and model orchestration ensuring data quality and performance monitoring.

Collaborate to scale self-driving systems, build training frameworks, profile model performance, and evaluate emerging technologies for training and inference.

Design, develop, and deploy machine learning models for search/sort, cancellations, pricing, and content selection. Perform feature engineering, run A/B tests, collaborate on production deployment, and communicate results via dashboards to improve customer and financial outcomes.

Seeking a Senior Machine Learning Engineer to develop voice assistant solutions using ML and deep learning, optimizing for production environments. Responsibilities include designing ML pipelines, mentoring juniors, and collaborating with cross-functional teams.