Top Remote Machine Learning Engineer Jobs in Austin, TX

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.

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.

As a Machine Learning Engineer Intern, you'll enhance model performance, develop production-grade tools, and automate workflows while receiving mentorship from experienced ML professionals.

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

Lead complex AI/ML projects from conception to production, mentoring teams, performing data analysis, and establishing AI/ML best practices in healthcare.

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 a Senior Staff Machine Learning Engineer, you'll build production models, improve machine learning features, and ensure data infrastructure for fraud detection and more. You'll leverage your extensive experience in machine learning and collaborate to drive product intelligence.

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.

This role involves designing and building advanced ML models to protect against fraud and enhance user experience while mentoring lower-level engineers and influencing technical roadmaps.

The role involves designing, developing, and deploying machine learning models for healthcare applications, collaborating with cross-functional teams, and optimizing model performance.

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

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 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.

The Lead AI/ML Engineer develops AI approaches for healthcare, builds ML models, conducts experiments, collaborates with teams, and ensures compliance with policies.

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.

The Principal Machine Learning Engineer shapes the machine learning strategy and architecture, leads initiatives, mentors engineers, and influences technical decisions at SharkNinja.

As a Machine Learning Engineer in the Risk AI/ML team at Coinbase, you'll develop, enhance, and deploy ML models to prevent fraud and improve security for users. This role involves end-to-end model ownership, responding to threats, and collaborating with various teams to create automated defenses.

As a Machine Learning Engineer, you'll enhance ML productivity, improve model deployment, and implement algorithms for credit decisioning systems.

As a Staff Machine Learning Engineer, you will develop and maintain ML models for decision-making, optimize pipelines, and collaborate with a diverse engineering team.

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

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.

Dandy seeks a Machine Learning Engineer to develop 3D computer vision models using SOTA methods, collaborate with product teams, and implement MLOps pipelines.

The role involves building computer vision models, researching deep learning methods, handling large datasets, and implementing MLOps best practices.

Design and implement AI/ML systems for healthcare challenges, manage machine learning systems, and develop data pipelines for real-time insights.

Design and build ML features using LLMs, collaborate on technical architecture, and ensure safety and performance of deployments.