Top Remote Machine Learning Jobs in Austin, TX

The role involves enhancing developer tools for GM's AV engineers, addressing pain points, and mentoring team members to improve productivity and maintain quality code efficiency.

As a Senior to Principal Machine Learning Engineer, you'll lead the architecture and development of the Agentic AI platform, focusing on LLMs. Responsibilities include enhancing LLM performance, designing evaluation methodologies, and establishing safety protocols for LLM use.

The Machine Learning Engineer role involves designing, implementing, and deploying ML solutions, focusing on LLMs and collaboration with engineering teams.

Develop and implement AI/ML solutions for healthcare claims processing, collaborating with data scientists to enhance system capabilities and automation.

Lead a team of ML engineers in developing advanced personalization systems. Balance technical leadership with hands-on model development, focusing on system architecture and improvements.

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.

Lead the Auto-Bidding team's technical vision, optimize recommendation and forecasting systems, mentor a high-performing engineering team, and drive technical projects in ad technology.

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

Analyze complex datasets, build machine learning models, and collaborate with teams to deliver data-driven insights in a remote-first culture.

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

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

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.

Lead the Embeddings Platform Team, architecting and maintaining foundational ML embeddings, driving projects, and building a high-performing team to support machine learning initiatives across Reddit.

As a Staff Applied Machine Learning Engineer, you'll design and implement LLM applications, integrating ML features to enhance user experiences and scalable services.

As a Principal ML Engineer, you will establish the technical vision for personalization at Launch Potato and drive alignment across ML teams while solving complex challenges and mentoring engineers.

The Principal ML Engineer establishes the technical vision for personalization and designs ML solutions that drive company strategy. Responsibilities include solving ML challenges, leading cross-functional initiatives, and mentoring senior engineers.

Lead the technical vision for personalization at Launch Potato, architecting ML solutions and influencing strategy while mentoring senior engineers.

Lead the technical vision and strategy for personalization at Launch Potato, solving complex ML challenges and mentoring senior engineers.

The role involves designing and building ML applications, leading teams, and collaborating on data-intensive solutions using various technologies, while ensuring optimal performance and governance of ML systems.

The Senior Manager in ML Engineering will lead design and implementation of ML applications, optimize systems, and collaborate with cross-functional teams for data solutions.

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 Principal ML Engineer will define and lead the ML architecture and strategy, solve complex challenges, and mentor engineers across the company.

Lead the technical vision for ML systems focused on personalization, architecting solutions, solving complex challenges, and mentoring senior engineers.

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