Top Artificial Intelligence Machine Learning Engineer Jobs in Austin, TX

The Staff Machine Learning Engineer will lead the development of advanced AI models, collaborate with teams, conduct research, and mentor junior engineers.

The Machine Learning Engineer will prototype and evaluate LLM features, collaborate with teams, contribute to technical design, and measure success metrics.

The AI Intern will work on integrating AI systems into Advantest's platforms, experiment with LLM configurations, and evaluate model performance to enhance user experience.

Intern will explore AI/ML techniques for engineering data, develop AI-driven approaches, prototype and test AI models, and participate in technical discussions.

Lead and execute applied AI/ML projects: translate ambiguous business problems into technical approaches, architect and validate models and pipelines, engage clients, mentor small teams, ensure code and deliverable quality, and contribute to business development and technical strategy.

Design and implement compiler optimization algorithms for deep learning inference, collaborate with framework and GPU architecture teams, define public APIs, and deliver high-performance AOT and JIT compilation with reduced memory and fast build times.

As a Staff Machine Learning Engineer, you'll develop, implement, and optimize ML models to enhance personalized customer experiences, collaborating across teams.

The role involves developing and maintaining machine learning models and infrastructure, defining technical vision, and leading cross-functional initiatives for scalable ML systems.

As a Staff ML Research Engineer, you will develop and optimize ML algorithms for drug discovery, transitioning high-impact prototypes into robust products and managing software development across the lifecycle.

As a Cloud Machine Learning Engineer at Hugging Face, you will build ML solutions leveraging cloud technologies, integrate models, design APIs, and contribute to documentation and community advocacy.

The Staff Machine Learning Engineer will enhance Quora's recommendation systems, lead machine learning projects, and own end-to-end ML processes.