Top Remote Machine Learning Jobs in Austin, TX

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

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

As a Software Engineering Intern, you'll develop features for user-facing products, work on API platforms, and design data pipelines while gaining hands-on experience in AI technologies.

Design and scale systems for personalization and ranking using ML. Mentor engineers and lead initiatives in a consumer-focused environment, leveraging AI tools.

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

As an Applied Scientist, you will design and implement machine learning models, develop personalized systems, and enhance decision-making through AI technology to improve user experience and business operations.

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.

Lead the creation and optimization of machine learning algorithms, develop and refine production-grade models, and drive testing of innovative algorithms using historical data.

Lead the design and implementation of advanced ML systems at Airbnb, mentoring engineers and shaping concepts into impactful products.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

As a Senior Machine Learning Engineer, you will enhance diffusion models, conduct research, collaborate on system implementations, and communicate findings effectively.

Develop and implement large-scale machine learning models to enhance user ad predictions and better understand user interests through data mining and collaboration with product teams.

As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.

Lead the Applied ML team's experimentation efforts, mentoring scientists and engineers to improve AI-driven methodologies and collaboration across various product areas.

As a Staff Machine Learning Engineer, you will optimize Quora's ad products by applying machine learning algorithms, taking ownership of systems, and collaborating across teams.

As Director of AI/ML, lead the ML organization, set technical vision, mentor a high-performing team, and contribute to model development and production deployment.

As a Machine Learning Engineer, you will develop and operationalize models for content understanding and discovery, collaborating with cross-functional teams and stakeholders to solve impactful problems using machine learning.

The Sr. Machine Learning Engineer will build tooling and services for ML and generative AI solutions, focusing on deployment, evaluation metrics, and cross-functional collaboration.

As an Associate Technical Architect in Machine Learning, you will design and develop advanced ML models on AWS, ensuring scalability and reliability while collaborating with cross-functional teams.

You will build and own end-to-end ML systems, focusing on training, evaluation, deployment, and integration with applications, while ensuring quality and efficiency.

The Senior Machine Learning Engineer will build and own production ML systems, manage end-to-end workflow, debug issues, and mentor others.

The Applied Machine Learning Engineer will develop AI-driven solutions, focusing on backend systems, AI integration, model deployment, and MLOps best practices, while collaborating with cross-functional teams.

As a Staff Machine Learning Engineer, optimize card pricing models, lead ML lifecycle, collaborate with experts, and enhance predictive features.

The Sr Cloud Machine Learning Engineer will develop data infrastructure, collaborate with data scientists, and implement advanced analytics solutions to enhance healthcare services.