Top Machine Learning Jobs in Omaha, NE

As a Senior ML Engineer, you'll own ML-driven features from modeling to deployment, drive innovation in generative AI, and mentor junior members.

The role involves leading ML strategy, architecting systems, designing algorithms, collaborating with teams, and mentoring engineers in AI for enterprise analytics.

The role involves product management of AI tools, collaborating with research, engineering, and design teams to develop and enhance products, focusing on user needs and market value.

The AI/ML Engineer develops AI features for Cengage's educational products, focusing on enhancing student engagement and learning outcomes through shipping production AI capabilities.

The DevOps Engineer will design, build, and optimize ML and data infrastructure on GCP, mentor a team, and ensure system reliability and performance.

The role involves improving recommendation systems using machine learning, developing end-to-end ML systems, and collaborating with engineers.

The Junior AI/ML Engineer will deliver machine learning projects, handle Python programming, and learn from a senior team member, focusing on real impact initiatives.

The Machine Learning Solutions Architect designs and implements data solutions, overseeing model deployment and ensuring robust performance and integration within customer environments.

As a Senior Software Engineer, you'll build and operate the ML platform, optimizing data operations, managing the feature store, and supporting ML initiatives while driving architectural roadmap decisions.

Develop AI/ML-powered features in ClickHouse Cloud, focusing on frontend and API architecture, UI/UX, and integrations with AI systems.

The Staff Engineer will architect and build AI and ML infrastructures, mentor engineers, and lead high-impact initiatives to enhance ML capabilities across Attentive's platform.

Develop novel machine learning methods to enhance computer vision solutions, identify areas for innovation, and translate research into scalable production systems.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

The AI Director will oversee ML bot development and implementation, identify AI opportunities, educate teams, and prototype AI solutions.