Top Machine Learning Engineer Jobs in Austin, TX

As Machine Learning Product Director, define ML strategy and manage product development for Attrition Risk Insights, enhancing customer engagement through predictive modeling.

Develop, validate, and deploy machine learning models and scalable ML pipelines. Preprocess and analyze data, run experiments, collaborate with senior engineers and stakeholders, and support model risk governance and regulatory-compliant AI applications (fraud detection, credit scoring, marketing analytics).

Lead the development of production-grade machine learning solutions, collaborating with cross-functional teams to solve complex business problems and deliver measurable impact.

The Machine Learning Engineer will prototype and evaluate LLM features, collaborate with teams, contribute to technical design, and measure success metrics.

The AI Intern will work on integrating AI systems into Advantest's platforms, experiment with LLM configurations, and evaluate model performance to enhance user experience.

The ML Data Engineer develops and maintains machine learning pipelines and systems, collaborating with teams to optimize manufacturing processes through data-driven insights and predictive models.

The role involves applying cutting-edge research in machine learning and deep learning to improve ad performance through various methodologies including modeling, optimization, and experimentation.

Responsible for training large-language models by reviewing, ranking, and improving AI-generated code. Requires strong software engineering skills.

The Director of Machine Learning will lead initiatives in fraud detection, incorporating AI techniques and managing ML model development, partnering with technical and business teams.

Develop and implement machine learning models for cybersecurity risk assessment and threat intelligence while collaborating with cross-functional teams.