Top Machine Learning Engineer Jobs in Austin, TX

The AI/Machine Learning Engineer will develop systems for automating health benefits decisions, integrating large language models with rule-driven patterns, and ensuring compliance with regulations.

The Machine Learning Engineer will develop software solutions, optimize data pipelines, and deploy machine learning models using cloud platforms and best practices.

Lead the advancement of embedding-based retrieval systems, focusing on multimodal models, model performance, and extensibility for various use cases.

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

Senior AI/ML Engineer responsible for designing, building, and deploying AI/ML systems, mentoring teams, and leading cross-functional collaborations to drive AI solutions.

As a Machine Learning Engineer at Shipwell, you'll build and scale AI-powered logistics solutions, maintaining data pipelines and ML infrastructure across the organization.

Lead technical strategy and architecture for machine learning systems, mentor engineers, and design scalable solutions for data mining and real-time inference.

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

The Machine Learning Engineer will develop and maintain scalable ML systems, collaborate across teams, and innovate solutions for real-time applications to enhance customer experiences.

Develop AI-powered solutions for personalized content and marketing. Collaborate with teams to optimize ML models and pipelines at scale, mentoring engineers and driving strategic growth initiatives.

The Machine Learning Engineer will develop and enhance search and retrieval systems, adapting search behaviors and integrating ML models for product recommendations, while managing infrastructure and data processing.

As an ML Ops Infrastructure Engineer, you will design CI/CD pipelines for ML, maintain deployment systems, and implement monitoring while collaborating with research teams to ensure model quality and performance.

The role involves building ML systems, improving models across product surfaces, and leveraging data for personalization and user engagement.

As a Machine Learning Engineer, you'll create and optimize production-ready ML solutions, manage the ML lifecycle, and conduct experiments.

As a Machine Learning Engineer, you will own the full lifecycle of ML from model development to production deployment, collaborating with teams to drive ML processes.

As a Senior ML Infrastructure Engineer, you'll design and build scalable platforms for ML inference workflows, collaborating with teams to optimize model serving and enhance system reliability.

The Senior Databricks AI/ML Engineer will design and deploy AI/ML solutions in the insurance sector, focusing on Databricks architecture, data pipelines, and MLOps workflows, while collaborating with various teams to operationalize models and optimize processes.

Develop and maintain scalable AI/ML architectures, collaborate on integrating solutions into products, and ensure compliance with industry standards.

As a Machine Learning Engineer, you will fine-tune transformer models, deploy machine learning solutions, and work with cross-functional teams on innovative projects.

The Senior Data Engineer will develop and deploy machine learning models, build end-to-end ML pipelines, optimize performance, and collaborate across teams to enhance AI capabilities at ClickUp.

As a Staff Machine Learning Engineer - AI Tech Lead, you will lead the design of AI systems for security operations, focusing on scalable architectures, AI safety, and mentoring. Responsibilities include overseeing technical evaluations, production workflows, LLM fine-tuning, and collaboration with teams to enhance AI capabilities.

This role involves developing and optimizing machine learning models for autonomy, managing datasets, enhancing training pipelines, and collaborating across teams to integrate ML solutions in autonomous vehicles and delivery robots.

The role requires a skilled Machine Learning Engineer to create complex models and AI solutions while collaborating with teams to enhance products and services.

The role involves building, deploying, and maintaining ML infrastructure, optimizing systems, and ensuring production reliability while collaborating with data scientists and product teams.

The Machine Learning Engineer will develop and deploy computer vision models, manage ML data infrastructure, and integrate systems for autonomous aerial platforms.