Machine Learning Jobs in San Jose, CA

Lead the design and implementation of GPU compute clusters for AI and HPC workloads, managing infrastructure and optimizing performance.

The role involves contributing to product strategy, implementing architectural roadmaps, enhancing customer experience, and managing analytics and profitability. An individual contributor role focused on cross-functional collaboration and success metrics.

The Lead Applied ML Research Engineer will research, develop, and deliver GenAI features, collaborating with teams to deploy robust AI models for enterprise use-cases.

Design, train, and deploy large deep learning models utilizing data from a fleet of vehicles to enhance autonomous driving solutions.

The Staff Machine Learning Engineer will research, design, and implement advanced deep learning algorithms for autonomous driving systems, ensuring robust, real-time performance and model optimization.

The Machine Learning Engineer will develop large-scale models for video understanding and generation, curate datasets, and collaborate with researchers to advance ML technologies.

Lead a team in developing AI/ML solutions within a data platform, focusing on innovation, technical excellence, and ethical practices while driving strategic growth.

Develop intelligent AI solutions for enterprise operations, design robust ML architectures, and mentor junior engineers. Collaborate with teams to deliver results.

As a Senior Machine Learning Engineer at Adobe, you'll design AI systems and build ML workflows, working closely with product and research teams to enhance customer experiences through innovative AI solutions.

The Applied ML Research Engineer will develop and deploy advanced video AI models, collaborating with product teams and Adobe Research to drive innovations in video understanding and content creation at scale.

Develop and operate high-performance computing clusters for AI/ML workloads, ensuring scalability, performance, and reliability through collaboration with cross-functional teams.

Develop and deploy ML-based perception algorithms for robotics, optimize pipelines, and collaborate across disciplines for integration.

Develop and maintain machine learning models for robotics applications, collaborate across teams, and contribute to innovative solutions in AI and mobility.

The role involves designing, developing, and implementing machine learning models while collaborating with teams to enhance services and deploy solutions effectively.

Lead the design, development, and implementation of advanced machine learning models, collaborating with teams to enhance services and drive insights.

The role involves designing and implementing machine learning systems for knowledge representation and temporal reasoning, focusing on organizational intelligence. Responsibilities include building LLM-powered pipelines, developing memory algorithms, and researching various ML techniques.

The role involves designing machine learning models, analyzing data for patterns, maintaining data workflows, and collaborating with cross-functional teams to drive business insights.

As a Sr. Machine Learning Engineer, you'll build agent capabilities, integrate AI systems, and partner to enhance creative workflows using LLMs and VLLMs.

Develop and optimize machine learning models, preprocess large datasets, deploy solutions, collaborate with teams, and monitor performance.

The role involves developing and implementing advanced machine learning models, deploying scalable ML/AI solutions, and communicating insights to both technical and non-technical audiences.

Lead architectural decisions and mentor engineers in developing scalable software solutions for the GenStudio team, driving innovation and technical strategy.

Lead full-chip implementation from RTL to GDSII focusing on timing closure, power optimization, and physical verification while using EDA tools and automation scripts.

Lead the design and deployment of machine learning models to enhance user experiences, collaborate with teams, and drive innovation in AI-powered tools.

The role involves building production ML models for voice AI, focusing on fine-tuning, deploying, and evaluating models to enhance human-like interactions.

You will build a search and assistant product, improve personalization, train models, and write robust code while mentoring junior engineers.