Top Senior Machine Learning Jobs in Austin, TX

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.

Lead cross-functional teams of machine learning engineers and data scientists, driving technical direction and fostering a collaborative environment to develop high-quality ML-driven capabilities.

Lead the design, development, and deployment of machine learning models, collaborating with teams and mentoring engineers. Focus on scalable ML workflows.

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

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

The Senior Machine Learning Platform Engineer will develop ML models, mentor engineers, optimize systems, and enhance ML infrastructure at Coinbase.

As a Senior Machine Learning Engineer, you'll develop models for risk identification, collaborate cross-functionally, and deploy ML solutions, ensuring performance monitoring and continuous improvement.

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.

Lead a team to advance performance marketing through machine learning and data-driven strategies, optimizing budget allocation and measuring impact.

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

The Senior Machine Learning Engineer will design, prototype, build AI systems, evaluate ML models, and improve Vectara's AI Agents with a focus on reliability and performance.

The role involves building AI technologies for customer service, developing ML systems, and collaborating with cross-functional teams to enhance user experiences.

As a Senior Machine Learning Engineer on the Perception Team, you will define technology direction, architect solutions for autonomous vehicles, collaborate with team members, and mentor junior engineers, contributing to high-stakes projects in autonomous driving.

The ML Engineer will work on RL frameworks, develop synthetic data engines, and maintain performance evaluations for a closed-loop drug discovery platform.

The role involves building a recommendation engine, designing ML systems, making data-driven decisions, and collaborating with leadership to enhance user experiences.

Develop and optimize machine learning models and workflows to enhance insurance processes. Collaborate on model integration, monitoring, and improvement while driving innovation in modeling techniques.

Research Engineer will conduct Machine Learning research to enhance localization and global entertainment, focusing on ASR, Speaker Diarization, and Audio Understanding.

Lead the ML and AI engineering team, strategizing and implementing AI solutions for business growth, mentoring staff, and collaborating across departments.

Build and optimize machine learning models for 3D dental applications, research state-of-the-art methods, and implement MLOps best practices.

Lead the design, execution, and analysis of machine learning-driven product experiments to optimize ordering systems. Collaborate with stakeholders and mentor teams.

Design and optimize machine learning systems, build scalable data pipelines, and run experiments to improve recommendations for Scribd's products.

The role involves applying machine learning and statistics to develop algorithms for RF domain challenges, requiring a strong mathematical foundation and cloud infrastructure experience.

The job involves developing and optimizing machine learning models, overseeing model risk, and collaborating with teams on AI-related projects.