Top Machine Learning Engineer Jobs in Austin, TX

The role involves developing ML methods for robotics, focusing on integration with learning-based planning and control under real-world constraints. Responsibilities include benchmarking approaches and contributing to system prototypes.

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 design, development, and implementation of advanced machine learning models, collaborating with teams to enhance services through AI/ML solutions.

The Machine Learning Engineer will develop and optimize models, manage datasets, enhance training pipelines, and collaborate across teams to innovate in autonomous vehicle technology.

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

The Senior ML Inference Engineer will design and operate a deployment platform for ML models onto autonomous vehicle hardware, collaborating with teams to enhance tools and address deployment issues.

Design and deploy ML solutions for clinical data, collaborating with cross-functional teams to translate healthcare challenges into scalable systems. Maintain reusable codebases and provide guidance to junior engineers.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

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

As a Machine Learning Engineer, you will design, train, and deploy ML models for motion planning, develop data pipelines, and integrate models for real-time use in autonomous vehicles.

The ML Engineer will develop motion planning models using ML techniques, simulate interactions for outdoor delivery robots, and collaborate across teams for integration.

Design, train, and maintain machine learning models for aerial target detection and classification. Oversee dataset pipeline and deployment of models, ensuring performance in real-world operations.

The Research Engineer will collaborate with scientists to develop and validate machine learning models for speech technologies, manage scalable training systems, and design tools for accessibility to non-technical users.

The role involves leading the technical development of a production ML application, mentoring junior engineers, and collaborating on architecture and strategy. The candidate will take ownership of the project and grow within the company as it evolves.

Lead architecture and engineering for production-grade ML in healthcare: design MLOps CI/CD, scalable low-latency inference for LLMs and classical models, build reliable data pipelines for FHIR/HL7/DICOM, manage cloud IaC and observability, ensure HIPAA/HITRUST compliance, and mentor engineering teams to operationalize agentic AI workflows.

The ML Engineer will contribute to the automated discovery engine, developing RL frameworks, synthetic data engines, and evaluating performance using proprietary datasets.

Design, develop, and deploy machine learning models; analyze large datasets; build scalable data pipelines and distributed computing environments; integrate ML solutions with cross-functional teams; optimize performance and support production ML infrastructure.

Lead the development of AI systems for Trustbridge and manage junior engineers, focusing on production deployment and technical strategy.

The Senior Staff Machine Learning Engineer will develop scalable ML infrastructure, define best practices, and enable rapid deployment of AI/ML models at Airbnb, collaborating with cross-functional teams.

Lead the development of ML models and prototypes for Edge AI/ML, integrate with mixed-signal systems, and optimize deployment. Collaborate with cross-functional teams and mentor engineers while exploring new ML trends and applications.

The Machine Learning Engineer will design and build systems that improve the AI shopping agent by using real user feedback, focusing on feedback loops and metrics to enhance user interactions and agent performance.

Design and deliver customer experience solutions using machine learning techniques, analyze customer data, implement ML algorithms, and automate processes.

As a Machine Learning Engineer, you'll design, build, and maintain models to detect security threats, ensuring model efficiency and aligning initiatives with business goals.

The Junior-Midlevel Developer will build and enhance Dumroo.ai's AI-powered education platform, collaborating on software components, data pipelines, and machine learning features.

The Forward Deployed ML Engineer will integrate AI/ML models into clinical software, assist in model fine-tuning, and engage with clients to ensure success in healthcare deployments.