Top Senior Machine Learning Jobs in Austin, TX

Build and optimize machine learning models for 3D dental applications, research state-of-the-art methods, and implement MLOps best practices.

Lead the design, execution, and analysis of machine learning-driven product experiments to optimize ordering systems. Collaborate with stakeholders and mentor teams.

As a Senior Machine Learning Engineer, you will develop scalable ML solutions, collaborate with teams, optimize models, and implement best practices for deployments and infrastructures.

The Senior Applied Scientist II is responsible for designing and implementing ML models to optimize the supply chain, collaborating across teams, and driving data-driven decision-making.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

As a Senior Machine Learning Engineer, you will design ML infrastructure, lead zero-to-one initiatives, collaborate on projects, and enhance scalability in the development of ML applications.

Design and build ML features using LLMs, collaborate on technical architecture, and ensure safety and performance of deployments.

Lead training, evaluation, and deployment of ML models for scene understanding and behavior prediction in autonomous vehicles.

You will train, evaluate, and deploy ML models for scene understanding and behavior prediction in autonomous vehicles, while collaborating with engineers.

As a Principal Engineer on the Behaviors team, you will guide the technology direction, lead complex initiatives, and mentor engineers to enhance autonomous vehicle capabilities through ML solutions.

Lead the development of ML solutions to enhance user experience at Babylist. Build recommender systems and personalization features from scratch, collaborating with a cross-functional team.

The job involves developing and optimizing machine learning models, overseeing model risk, and collaborating with teams on AI-related projects.

Senior Software Engineer role focused on building AI capabilities for an engineering AGI product. Collaborate with a team to integrate cutting-edge machine learning into real-world engineering systems and shape product design.

The Machine Learning Engineer will work on unstructured data classification and clustering, utilizing their expertise in AI systems and various programming languages.

The Senior Machine Learning Engineer will utilize deep experience and insights to enhance communication and digital interactions through advanced machine learning tools and algorithms, focusing on unstructured data.

The role involves applying machine learning and statistics to develop algorithms for RF domain challenges, requiring a strong mathematical foundation and cloud infrastructure experience.

The Senior Machine Learning Engineer will develop, deploy, and optimize machine learning applications, collaborating with cross-functional teams to enhance AI services.

Lead the development of AI-driven security workflows, integrate machine learning models, establish data pipelines, and mentor engineers.

Design, build, and optimize ML systems for recommendations at scale. Collaborate with teams on data pipelines, model development, and experimentation.

The role involves designing, building, and optimizing large-scale ML systems for personalized recommendations, focusing on data ingestion, model training, and collaboration with cross-functional teams.

The role involves designing and implementing scalable ML-based solutions, analyzing data patterns, and producing reports while staying updated on AI advancements.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

The Sr. ML Engineer will enhance Visa's AI platform across various environments, optimize code, develop solutions, and build high-performance systems using cloud technologies and machine learning techniques.

Lead the development and execution of ML platform strategies, manage a high-performing team, and enhance 3D deep learning applications.

Lead a team of Machine Learning engineers, drive technical direction, oversee large-scale ML systems and improve user experience for over 500M users.