Machine Learning Jobs in San Jose, CA

The role involves developing ML systems for enterprise workflows, focusing on user understanding, task prediction, and optimizing ML pipelines. Key responsibilities include designing scalable evaluation frameworks and collaborating with teams to deliver production-ready solutions.

As a Software & ML Intern, you will build data pipelines and cloud-based tools, collaborating extensively to develop scalable scientific software solutions.

As a Machine Learning Engineer/Scientist, you will develop ML systems for cryopreservation research, manage data pipelines, and deploy models for scientific insight.

The role involves building and maintaining machine learning infrastructure focusing on LLMs, designing scalable solutions, and mentoring teams.

Design and implement deep learning algorithms for autonomous driving, optimizing neural networks for real-time performance, and integrating multimodal data.

The role involves leading AI initiatives, solving machine learning challenges, mentoring teams, and collaborating on innovative solutions for manufacturing applications.

Lead the Inference ML team in developing tools and APIs for large-scale ML applications, enhancing performance and usability, while collaborating across engineering teams.

As an intern, you will research and implement algorithms in computer vision and machine learning, developing new features for Sony's digital imaging technology.

The role involves researching and implementing synthetic sensor simulation methods, analyzing sensor data realism, and collaborating with teams on autonomy performance.

Build and optimize the ML infrastructure for Coupang Ads Tech, improving the lifecycle of ML engineering for enhanced developer experience and efficiency.

The Machine Learning Engineer will develop and implement ML applications in generative AI, addressing integration challenges and evaluating model performance throughout the product lifecycle.

Interns will develop compiler optimization techniques for ML models, prototype programming interfaces, and implement solutions in C++ and Python.

The Staff Software Engineer will build and manage machine learning infrastructure focusing on LLMs, oversee DevOps processes, lead technical teams, and collaborate across functions.

Contribute to developing machine learning models for multi-scale biology, focusing on design, deployment and optimization across teams and technologies.

Lead architectural design for a scalable ML inference platform, mentor engineers, and drive best practices in MLOps and system performance optimization.

As an ML Infrastructure Engineer, you will build infrastructure for AI development, automate ML workflows, and enhance developer experiences while collaborating with various engineering teams.

As a Senior Machine Learning Engineer, you'll design and implement large-scale ML systems to enhance ad relevance and performance, mentor engineers, and collaborate with cross-functional teams in Mandarin.

The Staff Engineer leads engineering teams, focusing on product life cycle, architecture, design, and quality assurance while mentoring junior staff and enhancing processes.

As a Senior Staff Engineer, you will lead engineering teams, provide technical solutions, mentor junior members, and drive quality in enterprise applications with focus on voice technologies.

The Staff Engineer leads engineering teams to develop high-quality enterprise-class applications, mentoring junior members and ensuring the usability and performance of solutions.

Develop tools and services for the Anyscale platform, focusing on ML Ops, user interfaces, and critical infrastructure for scalable applications.

As a Machine Learning Research Scientist, you will develop advanced algorithms for behavior planning and prediction for autonomous vehicles, focusing on machine learning techniques to solve real-world challenges in trajectory generation and motion planning.

Build infrastructure for AI/ML environments, collaborate with teams for improvements, and interact with customers to enhance product features.

Lead the development of AI/ML infrastructure for simulations, optimizing systems for large-scale machine learning models and enhancing realism in autonomous driving.

Lead AI strategy and implementation, design AI systems, oversee model development, ensure ethical AI practices, and provide technical direction to teams.