Machine Learning Jobs in San Jose, CA

Lead development of AI/ML systems for robotics and manufacturing, implementing machine learning architectures and collaborating with cross-functional teams.

Design and optimize machine learning infrastructure, develop high-performance systems for AI model serving, and ensure model training and evaluation scalability.

Lead strategic initiatives and drive product design for AI-driven user experiences, collaborating with multidisciplinary teams to enhance productivity.

Join the Inference team to implement features and improvements for model serving on a GPU platform, focusing on performance and reliability.

This role involves leading AI initiatives, developing and implementing AI solutions, mentoring teams, and shaping GM's AI research agenda.

Lead the development of AI/ML systems for TIDAL, enhancing user experience through personalized recommendations and playlists while collaborating with cross-functional teams.

The Staff ML Engineer will design cloud-agnostic ML compute platforms, collaborate with teams, ensure efficient model deployment, and lead technical initiatives.

The Senior AI/ML Tooling Engineer will develop tools for analyzing ML model performance, collaborating with engineering teams, and optimizing training and inference.

Lead end-to-end machine learning solutions for autonomous driving, mentor engineers, design advanced models, and ensure safety and reliability in diverse scenarios.

As a Senior AI/ML Engineer, you will design and deploy advanced machine learning models for autonomous vehicles, collaborate with teams, mentor engineers, and drive innovation in onboard ML systems.

Lead engineering initiatives in Responsible AI, collaborate on bias mitigation in ML applications, mentor engineers, and define technical strategy.

TigerGraph seeks individuals to promote their scalable graph database technology used for analytics and machine learning across various industries.

Data Scientist at Tapestry utilizes analytical excellence to interpret large datasets, providing insights for better decision-making and efficiency in energy operations.

The role involves developing and deploying perception and deep learning models for autonomous driving, optimizing data pipelines, and conducting research in perception algorithms.

Lead a development team to prevent collision scenarios in autonomous vehicles, focusing on safety-critical systems through innovative algorithm and validation strategies.

The Principal Product Manager will oversee the strategy and execution of initiatives in AP and Expense Automation, collaborating with teams to innovate AI-driven financial operations for enterprises.

Lead the integration and maintenance of autonomous forklifts at customer sites, providing customer support and optimizing system performance with significant travel requirements.

The Onsite Lead Tester is responsible for linguistic quality at an account level, coordinating the linguistic team, client engagement, and managing linguistic assets.

The Research Scientist will explore AI/ML research questions, collaborate across functions, publish in top venues, and lead impactful initiatives in Machine Learning and Inference Research.

The role involves architecting solutions across multiple services, building scalable systems, and engaging in all software development aspects, with a focus on Generative AI and ML infrastructure.

As an intern at Adobe Research, you will tackle research problems, develop algorithms, run experiments, and present your findings under a mentor's guidance.

The intern will conduct research on AI's impact on HR, analyze data for improving manager experiences, and design personalized journey prototypes.

The Robotics Intern will develop and integrate algorithms for mobile manipulation tasks, leveraging machine learning and computer vision for efficient robot operation in real-world scenarios.

The Staff Machine Learning Systems Researcher will model performance of Lightmatter systems, collaborate on designs, publish research, and stay updated on ML advancements.

The role involves implementing AI applications, collaborating with hardware architects, optimizing algorithms, and researching emerging AI technologies to improve engineering workflows.