Top Machine Learning Jobs in Phoenix, AZ

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

As a Software Engineer, you'll enhance the user experience of ML tools, optimize workflows, and collaborate with product managers on ML infrastructure projects.

The role involves developing machine learning models for Netflix's Studio, collaborating with teams, and scaling ML solutions for data analytics.

As a Principal Machine Learning Engineer, you will design and develop machine learning applications, lead teams, and ensure project management excellence while engaging with clients.

Design and implement foundational machine learning systems, develop conversational interfaces, and improve existing generative AI solutions for hardware engineering.

Design and develop machine learning infrastructure and models, guide teams on data lifecycle, and build scalable services while collaborating closely with cross-functional teams.

Lead ML projects to optimize search and recommendations at Airbnb, collaborating with cross-functional teams to enhance user experience and business impact.

Develop and enhance embedded software for ML applications, collaborating with various teams to improve system performance and reliability.

Collaborate with ASIC engineers to develop ML-powered tools for physical design, enhancing PPA and reducing turnaround time in chip implementation.

As a Machine Learning Engineer, you'll build scalable ML systems for personalized recommendations, collaborating with data scientists and cross-functional partners.

As an AI/ML Engineer, you will develop LLM-driven applications, enhance the GenAI platform, and contribute to AI strategy and production code deployment.

The Senior Machine Learning Engineer will develop ML platforms, optimize model lifecycles, lead initiatives, and maintain code quality, collaborating with Data Science teams.

The role involves building scalable AI features, optimizing machine-learning pipelines, evaluating LLM outputs, and ensuring compliance with data governance standards.

Develop and deploy ML models for personalization and optimization, analyze performance, and collaborate with product teams to enhance user experiences.

The role involves building and maintaining ML pipelines, optimizing workflows, and contributing to product strategy with a focus on usability.

The role involves developing and optimizing intelligent agents using large language models, collaborating with the team, and solving technical problems.

Lead the development of advanced recommendation systems and ML pipelines. Collaborate with cross-functional teams to enhance user engagement through optimization of machine learning models at scale.

The Senior Full Stack Engineer will develop AI/ML features in ClickHouse Cloud, integrating databases with AI capabilities, ensuring robust API design, and building user-friendly interfaces.

This role involves designing, developing, and scaling machine learning systems for payment flows and recommendations, leading technical initiatives, and optimizing complex financial decision systems.

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.

The Staff Machine Learning Engineer will develop and maintain MLOps tools, optimize model performance, and collaborate on ML system architecture with a focus on enhancing developer experience.

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.

The Senior Machine Learning Engineer will develop ML infrastructure, deploy ML models, monitor performance, and mentor junior engineers. Collaboration with cross-functional teams is essential.

The Staff Machine Learning Engineer will design, develop, and deploy scalable ML algorithms, lead experimentation, and collaborate across teams to enhance AI solutions.

Lead the design and implementation of machine learning platforms at Yahoo, focusing on architecture, governance, and system performance while mentoring teams and influencing industry trends.