Top Senior Machine Learning Jobs in Kansas City, MO

Lead a team of ML engineers and software engineers focused on Ads Content Understanding, driving innovation and efficiency in Ads Monetization.

Design and implement ML infrastructure for scalable deployment, collaborate across teams, optimize ML systems, and enhance tooling.

The Staff Software Engineer will lead the design and architecture of the AI/ML platform, mentor engineers, and drive technical direction for MLOps infrastructure in healthcare automation.

Lead the architecture and development of AI and ML features, design evaluation frameworks, and mentor team members to enhance ML-driven product experiences.

Drive cross-team engineering efforts to improve user experience on Homefeed by implementing large-scale machine learning systems and enhancing data processing efficiency.

The Principal Product Manager will define and execute strategies for machine learning-driven search suggestions, working cross-functionally to enhance search experiences and align with business objectives.

As an ML Engineer, you will build and productionize predictive models for ad inventory and campaign performance, contributing to the growth of Netflix's ad platform.

Develop and deploy machine learning models for real-time ad systems, optimizing inventory management, targeting, and campaign effectiveness for Netflix's advertising platform.

Lead the design and delivery of ML infrastructure and models, mentor engineers, and drive innovation in AI-powered intelligence at Upwork.

Lead the architecture and development of machine learning systems for personalized care, treatment intelligence, and automation at scale. Collaborate with cross-functional teams and mentor engineers.

Develop and deploy machine learning models for fraud detection and prevention, collaborating with teams and ensuring model performance over time.

The Senior Machine Learning Engineer will develop full-stack tools, collaborate on research, and build production ML systems, optimizing infrastructure for AI startups.

Design and implement machine learning models to improve Risk and Fraud detection systems. Lead technical strategy and partner with operations to address rapidly evolving challenges.