Machine Learning Jobs in Sunnyvale, CA

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

As a Machine Learning Engineer, you will develop models for NLP and code-generation systems, analyze data, and improve AI performance using advanced algorithms. You'll manage the entire ML lifecycle and ensure effective communication of model benefits across the organization.

Lead the development and deployment of advanced machine learning models focusing on NLP, while ensuring model integrity and communication with stakeholders.

Develop and deploy machine learning algorithms for planning in autonomous trucks, ensuring safety and real-time efficiency.

The role involves exploring ideas in deep learning, managing machine learning project life cycles, and collaborating on autonomous driving technology.

Seeking a Principal Software Engineer for architecting ML systems, unifying codebases, and leading cross-team architecture for Waymo's foundation models.

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

Lead the development of AI/ML infrastructure for simulations. Collaborate on realism models, scale distributed systems, and ensure alignment with business goals.

The Machine Learning Engineer will build and scale ML infrastructure, drive model performance, and ensure reliability while collaborating with various teams to optimize feature engineering pipelines and champion best practices.

The role involves developing large-scale data processing pipelines, automating data selection, and collaborating on ML model improvements to enhance vehicle performance and safety.

Lead junior team members in test planning, automation, and execution of software for AI compute engine, developing test suites and infrastructures, and collaborating on test coverage and results.

Design and manage the architecture of next-generation System-on-Chip for ML accelerators, ensuring optimal integration and performance trade-offs.

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

Design and implement a scalable MLIR-based compiler framework for cloud-based AI inference, collaborating with multiple teams to optimize model deployment.

As a Machine Learning Engineer, you will develop and enhance ML methods for 3D object detection and monitor ML systems in production, focusing on real-world applications and optimizing task performance.

The Senior Machine Learning Engineer will enhance recommendation systems, employ AI/LLM technologies, and drive AI innovation for content discovery and user engagement.

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

The Applied Machine Learning Research Scientist will translate ML techniques into scalable systems, improve LLM performance, and optimize workflows while collaborating closely with researchers and engineers.