Artificial Intelligence Jobs in San Jose, CA

As a Backend Engineer at Brain Co., you will design, build, and operate backend services and data pipelines for AI products, focusing on robustness and scalability. You'll collaborate across teams and own the full service lifecycle while ensuring high availability and performance. You should have 3+ years of experience in production backend systems and a strong foundation in APIs and distributed systems.

The AI Intern will support the deployment of multimodal models onto vehicle-grade platforms, assist with model optimization, and help ensure reliable performance in autonomous driving applications.

Lead the development of AI applications, ensuring high reliability and performance while collaborating with teams to identify use cases and implement scalable solutions. Drive AI methodologies, governance, and continuous improvement in the organization.

The intern will analyze driving data, classify scenarios, build workflows for vector search, and support data mining for VLA models.

The Founding Engineer will architect and build an AI-native compliance platform, focusing on document processing, AI systems, and productionization, while collaborating with the founding team.

The Program Manager will orchestrate product launches, ensuring cross-functional alignment, managing risks, tracking key performance metrics, and driving organizational accountability for success.

Lead and architect AI initiatives, develop large-scale AI/ML systems, mentor teams, and drive engineering excellence across Altera.

Design, develop, and optimize algorithms for oneDNN targeting Intel processors and graphics. Conduct performance analysis and contribute to low-level tuning and optimization efforts, collaborating with cross-functional teams and engaging with the open-source community.

Lead the development of large-scale video foundation models for humanoid autonomy, focusing on training strategies and model evaluation for real-world applications.

Develop learning systems using reinforcement learning for autonomous robots, focusing on policy optimization and real-world application.

The Helix AI Engineer, Modeling will design core model architectures for AI systems, focusing on multimodal inputs and improving model capabilities for humanoid robotics.

The Helix AI Engineer will design, train, and deploy large-scale generative models, focusing on diffusion modeling for robots, while enhancing robot autonomy through perception and world modeling.

As a Helix AI Engineer focused on pretraining, you will design and train foundation models using multimodal data, improve generalization strategies, and optimize distributed training pipelines.

This role involves driving new client acquisition and revenue growth through full-cycle sales execution and relationship building with stakeholders, while maintaining pipeline tracking in CRM.

As a Founding AI Engineer, you will develop an AI-powered knowledge platform, focusing on backend systems, machine learning data pipelines, and optimizing tech stack for performance while participating in the entire product lifecycle.

The Senior ASIC Design Verification Engineer leads verification planning and execution for AI chip designs, collaborates with cross-functional teams, and innovates verification methodologies.

The AI Engineer will design and develop intelligent agents utilizing LLMs and orchestration frameworks, working on scalable AI systems and ensuring data quality.

The role involves leading AI-driven chip design programs, managing cross-functional teams, and ensuring timely project execution and quality delivery.

You will develop AI agents for verification tasks, enhance verification flows, collaborate with HW teams, and optimize algorithms.

The Senior Software Engineer will drive integration of NVIDIA Grove with open-source AI frameworks, develop production-grade software, optimize performance, and collaborate with teams for robust integrations.

Lead the evolution of NVIDIA Dynamo's distributed inference framework by defining product strategy, managing memory and KV cache, and ensuring hardware-software optimization.

The role involves designing and scaling observability platforms, developing telemetry pipelines, and collaborating with engineering teams to ensure the reliability and performance of AI/ML systems.

The role involves developing AI agents for verification tasks, collaborating with hardware teams, and optimizing algorithms for data processing while integrating AI optimizations into existing tools.

Conduct cutting-edge research on generative AI methods, focusing on biomolecular design. Collaborate with teams and publish findings.

Research and develop GPU-accelerated techniques for AI and financial workloads. Analyze and optimize performance on CPU/GPU architectures, collaborate with industry and academia, publish findings, and influence hardware and software design while supporting developer adoption.