Top Machine Learning Jobs in Austin, TX

The Senior Machine Learning Engineer will design and implement detection systems to improve email security, lead project execution, and mentor junior engineers.

Join TensorOps as a Junior AI/ML Engineer. Work on AI and ML projects, receive mentorship, and contribute to production-grade systems.

Design and implement machine learning bidding algorithms, evaluate their performance with large-scale data, and align them with business goals.

As a Staff Machine Learning Engineer - AI Tech Lead, you will lead the design of AI systems for security operations, focusing on scalable architectures, AI safety, and mentoring. Responsibilities include overseeing technical evaluations, production workflows, LLM fine-tuning, and collaboration with teams to enhance AI capabilities.

As a Machine Learning Engineer, you will fine-tune transformer models, deploy machine learning solutions, and work with cross-functional teams on innovative projects.

Design and deploy machine learning models for autonomous vehicles, focusing on data tagging, dataset curation, and model validation.

As a Sr. AI/ML Engineer III, you will design and implement reinforcement learning algorithms, integrate them into simulation environments, and evaluate their performance. Collaborating with engineering teams, you will ensure the maintainability and transparency of AI components while communicating results and recommendations clearly.

Join DICK'S Sporting Goods as a Senior Machine Learning Engineer, focusing on AI-driven search solutions that enhance decision-making and engagement across the organization.

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

As a Senior Machine Learning Engineer, you'll design and implement ML models, develop data pipelines, and collaborate on AI features at Mural.

Build and deploy ML systems that detect fraud and automate security decisions, while collaborating with cross-functional teams.

Develop and optimize machine learning models for financial and operational workflows at Netflix, ensuring model reliability and integration with studio applications.

The Staff ML/AI Platform Engineer will design, prototype and deploy AI/ML models, optimize pipelines, mentor junior engineers, and collaborate closely with other teams to develop machine learning solutions.

The Machine Learning Engineer will fine-tune and deploy Large Language Models, optimize ML models, maintain data pipelines, and collaborate on AI features.

The Applied Scientist AI/ML Intern will work on building data pipelines, finetuning LLMs, and deploying AI models in a collaborative team environment.

Responsible for developing production-grade machine learning systems, managing end-to-end ML pipelines, and collaborating on integration with applications.

The Principal Machine Learning Engineer will build and maintain end-to-end ML systems, fine-tune models, and manage production deployments, ensuring robustness and efficiency.

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 role involves developing ML algorithms for autonomous driving, including training models, evaluating performance, and improving behavioral models.

As an AI/ML Engineer, you will design, train, and deploy machine learning models, optimize model performance, and collaborate with cross-functional teams to integrate AI capabilities into products.

As a Machine Learning Engineer, you'll architect data pipelines, build ML training workflows, integrate event streams, and collaborate with teams to improve model performance and ensure compliance.

The Staff Machine Learning Engineer will develop ML models and infrastructure for personalized experiences, collaborating with teams to implement end-to-end solutions and ensure high quality in systems development.

As a Senior Machine Learning Engineer, you'll create ML models to combat fraud on Airbnb, collaborating across teams to enhance user safety and confidence.

The Machine Learning Engineer will execute the full ML lifecycle, collaborating on model implementation and improving customer experiences through data-driven insights.

Lead the end-to-end machine learning lifecycle for AI products, managing data pipelines and model development to optimize performance and accuracy in production.