Top Machine Learning Engineer Jobs in Austin, TX

The Staff Machine Learning Engineer will lead the development of AI solutions, ensure project delivery, and manage technical teams while interfacing with customers. Responsibilities include designing data pipelines, overseeing machine learning model development, and facilitating customer engagement.

Design and implement scalable ML infrastructure solutions, mentor junior engineers, own technical projects, and collaborate across teams to solve complex AI/ML problems.

As a Senior AI/ML Engineer, you'll enhance developer productivity by leading CI solutions, mentoring engineers, and implementing scalable systems.

The Principal AI/ML Engineer will lead the AV ML Infra team at GM, focusing on developing scalable ML infrastructure and guiding cross-functional collaboration while driving technical projects from inception to completion.

The Staff AI/ML Engineer will design and implement scalable ML infrastructure solutions, lead projects, mentor peers, and enhance ML productivity at GM.

The Machine Learning Engineer will lead the development of a semantic intelligence platform, building knowledge graphs and AI software to enhance data accessibility and business insights.

As a Machine Learning Engineer, you will perform analysis on healthcare data, develop and deploy clinical machine learning models, and collaborate with various stakeholders.

Design, develop, and deliver machine learning models for clinical data. Collaborate with stakeholders and optimize production ML systems.

The Principal Machine Learning Engineer will develop ML algorithms and optimize performance on ARM computing platforms, collaborating across hardware, software, and ML algorithms, while focusing on performance, power, and area.

The Staff ML Engineer will design and operate Samsara's ML platform, collaborating with teams to enhance ML features and improve safety outcomes. Responsibilities include overseeing system reliability, leading technical direction, and mentoring engineers.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

The Staff Machine Learning Engineer will design backend software components, ensuring platform performance and reliability, while integrating GPU hardware and leading large initiatives within GM's AI ecosystem.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

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.

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

Lead the development of automated ML-driven map reconstruction systems. Architect and implement pipelines to validate and maintain map primitives, ensuring reliability across large-scale deployments.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

The Machine Learning Engineer will design, build, and maintain production machine learning systems, focusing on scalability, reliability, and integration with existing products. Responsibilities include developing ML pipelines, establishing ML Ops best practices, and collaborating on product capabilities.

The Principal ML Engineer at Agero will develop and productionize a Dispatch System using ML models, optimize decision-making processes, and lead a team to improve operational performance.

Lead design and implementation of enterprise-grade AI systems, architect AI infrastructure, and drive technical strategy for AI-powered products primarily for military applications.

The Senior Software Engineer will lead projects focused on building an AI platform for managing models, collaborating on features, and maintaining high performance in a scalable environment.

Lead development of scalable ML infrastructure, focusing on compute for simulation, data labeling, and data generation. Collaborate with ML engineers, set technical roadmaps, ensure system reliability, and research advanced computing techniques.

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

The Machine Learning Engineer develops production ML algorithms and recommendation systems, collaborates with teams, and optimizes user experiences.