Software Engineer Jobs in San Jose, CA

Lead design and implement a global public cloud SRE platform for AI and compute workloads. Own architecture and production engineering for observability, cluster health, remediation, lifecycle, secrets, CI/CD, backup/DR, and automation. Collaborate with cross-functional teams to build scalable, reliable multi-region services and run them in production (on-call).

Design and implement developer tools for GPU-based 3D graphics and neural rendering. Improve existing tooling, collaborate with compiler/driver/research teams, write high-performance C/C++ code, document designs, estimate tasks, and develop test plans with QA.

Lead development and migration to a workflow-as-code management plane (Temporal) to provision and operate a global fleet (100k+). Build idempotent, replay-safe workflows, orchestration-ready platform APIs, AI/ML-driven SRE features, and deep telemetry for explainable, auditable fleet operations.

Lead quality engineering and test automation for Zscaler's distributed security cloud. Use AI-assisted frameworks to generate and execute test plans, validate bug fixes, and collaborate with developers and product. Support core cloud operations including phased rollouts, feature enablement, alert handling, capacity planning, performance benchmarking, chaos testing, and diagnosing complex distributed failures to maintain high availability.

Build, test, and maintain software across full-stack, backend, infrastructure, data pipelines, and ML infrastructure to support autonomous trucking. Develop web interfaces, backend services, APIs, and tooling; improve reliability, observability, CI/CD, and deployment; participate in code reviews, debugging, and cross-team collaboration while learning new technologies.

Build and maintain end-to-end mobile systems for iOS and Android, shipping production-quality code, collaborating cross-functionally, applying blockchain/crypto knowledge, using AI tools to improve workflows, conducting code reviews, and mentoring and onboarding team members.

Design and implement real-time MAC data-plane software for high-throughput satellite links. Build packet-processing pipelines, queue and buffer management, retransmission and loss recovery, and integrate with PHY, modem, FPGA, DMA, and SoC hardware. Optimize for low latency and high throughput using zero-copy, scatter-gather, lock-free structures, and hardware offload. Lead architecture through prototyping, hardware integration, performance qualification, and operational deployment while diagnosing timing and synchronization issues.

Develop and prototype high-performance CUDA-based deep learning systems and custom kernels. Architect and optimize distributed, cluster-scale training and inference pipelines, analyze hardware-software performance bottlenecks, build profiling and runtime tools, and collaborate with researchers, compiler and driver teams to transition prototypes into frameworks or products.

Lead a portfolio of cloud-native, full‑stack projects and a team of developers to build distributed microservices and regulatory solutions. Collaborate with product managers, mentor engineers, evaluate and write code, and deliver scalable AWS/GCP/Azure-based systems using languages like Java, Python, Go, Node, and Scala with Docker and Kubernetes.

Own and maintain the backend stack: build APIs and services in Node.js, manage deployments with Docker/Linux, design scalable REST APIs with Swagger, collaborate with hardware/frontend teams, and prepare sensor datasets for AI/ML pipelines with an eventual path to Lead AI Engineer.

The role involves building consumer products, optimizing user experience, architecting product infrastructure, and influencing company strategy in a collaborative environment.

Design, prototype, develop, and debug software for semiconductor equipment. Provide reliability and performance engineering for CIM products, automate test methodologies with AI tools, perform root cause analysis, develop documentation and test procedures, conduct proofs-of-concept, and communicate with internal/external stakeholders.

Build and operate core backend services, APIs, and platform components for enterprise AI; integrate LLMs, retrieval and agent workflows; ensure reliability, observability, testing, and scalability; collaborate with research, product, and design to productionize AI capabilities.

The role involves designing diagnostic software for NVIDIA's systems, collaborating with teams to ensure software integration, and evaluating technical standards for product lifecycle phases.

Design and develop software solutions for data center servers, focusing on Linux kernel modifications, device drivers, and system optimizations while directly collaborating with Cloud Service Providers.

Lead the architecture and optimization of automotive platform software, collaborating with hardware and software teams to improve performance and reliability while mentoring engineers.

The role involves developing NvSci software for cross-platform integration, enhancing APIs, optimizing performance, and ensuring automotive safety standards, while leading complex system feature development.

The role involves developing AI systems software, implementing and optimizing kernels for AI workloads, and collaborating on deep learning frameworks and libraries.

Lead development and maintenance of node provisioning, OS image build/packaging, and nodepool lifecycle for NVIDIA Kubernetes Engine. Build CAPI providers, BYON onboarding, hardened image pipelines with automated CVE remediation and compliance gating, and automated test suites. Troubleshoot node-layer failures at scale, collaborate with upstream Kubernetes/CAPI communities, and ensure reliable GPU-optimized node operations across large clusters.

Design, develop, and optimize core AV platform software including sensor drivers, data streaming/recording, GPGPU-accelerated processing, and vehicle interfaces. Collaborate with vendors, perform in-vehicle testing, and support large-scale data collection to deliver low-latency, high-performance autonomous vehicle software.

Develop and bring up CUDA drivers for new GPU silicon across pre-silicon simulation to production. Design, implement, test, and stabilize CUDA features with HW and SW teams, write maintainable cross-platform kernel and system software, debug multithreaded systems, and contribute to CUDA APIs and programming model improvements.

Design and develop core components and performant frameworks for an autonomous driving platform, interfacing with vehicle sensors, optimizing parallel/GPGPU code (CUDA), performing in-vehicle tests and data collection, writing production C++ code, and ensuring quality and safety compliance.

Lead integration and productization of NVIDIA DRIVE autonomous vehicle platform software. Architect platform software, tools, and filesystem customization, enable automated build/test/release workflows, and debug application-to-kernel issues on embedded hardware while coordinating cross-functional teams and engaging customers to meet production release timelines.

Design, develop, and maintain autonomous driving platform and middleware. Integrate vehicle sensors, implement sensor abstraction layers, build data recording/mining and service frameworks, optimize performance and data serialization, improve startup UX, and collaborate with hardware, algorithms, cloud, safety, and platform teams to deliver scalable, high-performance system software for AV fleets.

Join Ema as a Software Engineer to design and develop user interfaces for web applications, collaborating with product managers and UX designers, and integrating APIs.