Top Machine Learning Jobs in San Antonio, TX

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

As an ML Engineer, you will build and deploy machine learning models for autonomous robots, collaborating with ML scientists and engineers to enhance AI capabilities.

Develop and optimize large-scale ML models and training pipelines for automating PCB layouts, collaborating on data pipeline design and novel architectures.

The Senior AI/ML Engineer will design and maintain scalable ML infrastructure, mentor data scientists, and ensure production readiness of AI models.

Design and deploy machine learning models for autonomous vehicles, focusing on data tagging, dataset curation, and model validation.

The engineer will design and maintain auto-bidding algorithms, optimize ad delivery systems, and collaborate on engineering projects for campaign performance.

The Solutions Architect for AI/ML at Snowflake will advise clients on best practices for Data Science workloads, design solutions, and build ML pipelines. Responsibilities also include working hands-on with SQL and Python, maintaining technical expertise and collaborating with teams to improve products.

The Senior Machine Learning Engineer will develop scalable ML systems, lead a team, mentor juniors, and work cross-functionally to enhance customer experience through machine learning solutions.

As a Senior Machine Learning Engineer, you will design and develop machine learning applications, conduct experiments, and mentor project teams, ensuring client satisfaction and leveraging the latest advancements in the field.

The Machine Learning Engineer will fine-tune and deploy Large Language Models, optimize ML models, maintain data pipelines, and collaborate on AI features.

The Staff Machine Learning Engineer will design and deploy ML models, build real-time model APIs, and collaborate across teams to drive user growth and revenue through AI/ML solutions.

The role involves developing scalable ML solutions, leading cross-functional discussions, analyzing knowledge data, and producing technical documentation to improve search relevance using AI and machine learning technologies.

Contribute to AI/ML capabilities for personalization in Yahoo Mail, develop tools for data processing, and collaborate with cross-functional teams.

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

Design, develop, and maintain algorithms for engineering applications, manage datasets, and implement machine learning workflows in an AI Copilot startup.

The Senior Machine Learning Engineer will develop ML platforms, optimize model lifecycles, lead initiatives, and maintain code quality, collaborating with Data Science teams.

The role involves building scalable AI features, optimizing machine-learning pipelines, evaluating LLM outputs, and ensuring compliance with data governance standards.

Develop and deploy ML models for personalization and optimization, analyze performance, and collaborate with product teams to enhance user experiences.

As a Machine Learning Engineer at Zillow, you will develop and implement machine learning models, prototypes, and algorithms, collaborating closely with scientists and engineers. You will focus on deploying applications, improving reliability, and fostering innovation in AI solutions.

Lead the development of credit risk models, collaborating with consultants and technology teams, and implement LLM-based agents for dynamic decision-making.

The Senior Machine Learning Engineer will build and operate ML systems, manage the model lifecycle, and mentor team members while ensuring sustainability data accuracy.

As an AI/ML Engineer, you will design, train, and deploy machine learning models, optimize model performance, and collaborate with cross-functional teams to integrate AI capabilities into products.

Responsible for deploying and improving MLE solutions, building production data pipelines, and writing scalable machine learning systems while collaborating with teams to drive strategy and communicate results.

The Lead Data/ML Engineer will design and maintain scalable data pipelines and AI systems, ensuring data reliability and collaboration with product teams.

The Applied Scientist Intern will develop and deploy AI models, build ETL pipelines, and collaborate to enhance AI quality in legal tech.