Top Remote Machine Learning Jobs in Austin, TX

As a Senior Machine Learning Engineer at CrowdStrike, you will innovate machine learning technology for data science, create scalable microservices, build data pipelines, and collaborate across teams to enhance the cybersecurity platform. You'll engage in ongoing learning, maintain coding standards, and contribute to a collaborative environment while mentoring fellow engineers.

As a Principal ML Infrastructure Engineer, you will define and drive the technical vision for Thumbtack's ML infrastructure, lead cross-functional initiatives, architect scalable ML systems, establish engineering standards, mentor teams, and align infrastructure capabilities with business objectives.

The Samsara ML Experience team is looking for an Applied Scientist to develop ML solutions that enhance the safety, efficiency, and sustainability of physical operations. Responsibilities include driving new ML initiatives, staying connected to industry and academic research, designing and optimizing services, and championing Samsara's cultural principles.

The AI Scientist will develop and implement innovative deep learning methods for chemistry, collaborating with biologists and chemists to advance drug discovery. Responsibilities include initiating new projects and creating state-of-the-art AI models for molecular modeling.

The Machine Learning Engineer will focus on enhancing search relevance and personalization on Instacart's platform by developing and optimizing machine learning models. Collaboration with cross-functional teams is vital to create scalable solutions while also contributing to research and thought leadership.

As a Machine Learning co-op, you'll work on developing and deploying machine learning algorithms to automate administrative clinical practices. You'll be part of an agile team, contributing to feature design, testing, and delivery of ML models, while collaborating with various stakeholders.

The Machine Learning Engineer at Liftoff will develop and train algorithms for real-time bidding, analyze inventory performance, and oversee experiments for optimization strategies. The role involves enhancing existing ML infrastructure, collaborating with engineering teams on data pipelines, and fostering a culture of engineering excellence.