Top Senior Machine Learning Jobs in Tucson, AZ

The role involves designing and implementing data and AI architectures, developing data pipelines, and integrating machine learning solutions while fostering Agile methodologies and collaboration.

The Senior Machine Learning Engineer will build and operate ML systems, manage the model lifecycle, and mentor team members while ensuring sustainability data accuracy.

The Senior Product Manager will lead the strategy for an AI assistant, ensuring compliance and user satisfaction while coordinating with cross-functional teams throughout product development.

Rocket Lawyer seeks an experienced AI/ML Software Engineer to enhance AI features in their platform, mentor developers, and collaborate across teams.

The role involves designing and implementing user-friendly interfaces, collaborating with data scientists on ML model deployment, and maintaining CI/CD pipelines for ML workflows.

Lead research on humanistic AI for autonomous systems. Collaborate with teams, design experiments, and publish findings in top-tier publications.

As a Senior Machine Learning Engineer, you will develop and deploy machine learning algorithms, collaborate on AI projects, and troubleshoot existing code.

Lead ML research and development, collaborating with engineers and clinicians to create enterprise-grade products and establish a research agenda while sharing insights through publications and presentations.

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.

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

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.

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

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

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.

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.

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

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.

The Senior Machine Learning Engineer will enhance fraud detection capabilities through ML technologies, improve model performance, and lead high-impact ML projects from experimentation to production.

This role involves deploying and optimizing machine learning models for autonomous vehicle motion planning, ensuring performance and reliability in production settings.

Lead the technical vision and architecture for machine learning and data systems, overseeing scalable infrastructure and collaboration across teams.

Lead and grow a global engineering team, drive technical strategy, and deliver value through innovative solutions while fostering a culture of growth and collaboration.

The Senior Machine Learning Engineer will design and implement ML solutions, collaborate with teams, and contribute to scalable infrastructure enhancements.

The role involves designing and developing machine learning infrastructure and models, consulting on best practices, and building scalable services for AI integration.