Machine Learning Jobs in Sunnyvale, CA

As an AI/ML Engineer, you will design and deploy models for real-world applications, optimize data pipelines, and engage with global leaders to enhance AI technology's impact across sectors like healthcare and government.

Develop and deploy machine learning models for agentic workflows, optimize AI systems for multimodal applications, and innovate fine-tuning techniques.

As a Staff Machine Learning Engineer, you will develop machine learning models and optimization algorithms for Coupang's advertising platform, focusing on improving ad targeting and engagement.

Responsible for designing and implementing scalable ML software solutions for Search & Discovery, processing massive datasets, and optimizing ML pipelines for real-time applications.

The role involves designing and developing machine learning infrastructure for annotation, evaluation, and training models, focusing on scalable systems and efficient data workflows.

Drive the quality strategy for Modular's engineering organization by implementing quality systems for AI infrastructure. Collaborate with teams, monitor quality processes, and enhance product excellence.

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

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.

Join Waymo's Simulator Team to develop ultra-realistic sensor data and perception simulation for autonomous vehicles using advanced ML technologies. Collaborate with foundational AI research teams and drive innovation in simulation realism.

Architect and develop a high-performance ML runtime for autonomous vehicles, optimizing for both onboard and offboard systems while collaborating with Waymo ML practitioners and enhancing tooling for performance analysis.

Design and oversee the development of robust data platforms for training and evaluating ML models, focusing on autonomous driving. Collaborate with multiple teams and optimize data processing pipelines.

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

As an MLOps engineer, you will develop optimized data pipelines, enhance data engine architecture, and integrate foundation models while working closely with DoD customers.

This role involves improving AI and ML infrastructure for researchers by identifying bottlenecks, optimizing performance, and collaborating with diverse teams.

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 a Staff Machine Learning Engineer, you will design, build, and deploy ML systems, optimize performance, and collaborate with teams to integrate AI solutions.

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

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

The role involves designing and optimizing bidding algorithms, enhancing real-time bidding systems, analyzing marketplace dynamics, and driving projects to deliver impact.

The Physical Design Engineer will lead efforts in solving physical design challenges, improve RTL-to-GDS methodologies, and integrate AI/ML solutions into CAD flows, focusing on performance and runtime improvements.

As a Staff Machine Learning Engineer, you will lead the development and deployment of AI models for autonomous driving, focusing on safety and reliability. Responsibilities include driving the roadmap, training models, and collaborating across teams.

The role involves deploying and optimizing LLMs, designing the ML serving stack, and ensuring high-performance GPU services for production readiness.

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

As a Machine Learning Engineer Intern, you'll bridge the sim-to-real gap in data for autonomous truck software, optimizing and integrating BEV features and supporting self-play reinforcement learning.