Software Engineer Jobs in Sunnyvale, CA

Design, build, test, and maintain enterprise integrations and automations across procurement, finance, and supply chain systems using MuleSoft and Zip iPaaS. Develop Python tools, write and optimize SQL, collaborate with stakeholders, ensure scalability and security, monitor production integrations, and contribute to documentation and DevOps practices.

Design, build, and scale cloud-native distributed systems and runtimes to deploy, run, fine-tune, and observe enterprise AI agents. Drive architecture, optimize model/infrastructure interactions, improve developer iteration tooling, enforce secure-by-design practices, and mentor engineering teams to deliver production-ready agent platforms.

Develop and operate large-scale, low-latency Azure cloud services for hardware health monitoring, anomaly prediction, telemetry, reliability, and performance. Evaluate and implement AI technologies, including LLMs, embeddings, RAG, and custom machine learning models, to improve firmware and hardware. Lead root-cause analysis, service restoration, testing automation, security and compliance, production deployment, and analytics reporting.

Design, build, and operate high-scale experimentation platform components for AI systems. Lead architecture, produce reliable, secure, and performant services, mentor engineers, collaborate with PMs and SRE/privacy/security partners, maintain on-call operations, and drive automation, observability, and experimentation best practices.

Develop GPU display system software from proof of concept through production, including architecture, algorithms, implementation, optimization, and debugging. Design features based on DisplayPort, HDMI, and eDP standards; influence GPU, SoC, and platform architecture; collaborate with hardware, software, and OEM/ODM teams; and deliver solutions under tight deadlines.

Design, build, and operate large-scale distributed systems in Go to ingest, process, and analyze file-based threat data. Work across storage, message queues, APIs, and data pipelines; improve reliability, observability, and performance; and integrate AI-augmented development practices with security researchers and engineers.

NVIDIA seeks a Senior Software Engineer to enhance its AI platform using JAX, focusing on performance optimization in deep learning frameworks while collaborating with applied researchers. The role requires strong programming, system design skills, and a proven ability to develop customer-facing solutions.

Design, build, and operate scalable IAM solutions across cloud, Kubernetes, SaaS, and internal systems. Lead end-to-end IAM projects: role design, privilege reduction, access reviews, SIEM observability, and automation to continuously de-risk access and enable secure engineering velocity.

Lead the design and development of high-performance AI networking software for NVIDIA BlueField DPU and ConnectX products. Manage hyperscaler technical engagements involving coding, system bring-up, performance tuning, failure analysis, and production hardening. Collaborate across engineering, product, architecture, and customer teams to translate needs into product features and roadmap improvements. Drive reliability, performance, debuggability, and tooling enhancements across firmware, drivers, operating systems, and applications.

Graduate software engineering interns will analyze autonomous driving behaviors, build automated pipelines for undesirable-event response, improve behavior-detection signals, and quantify driving performance. The role involves Python or C++, data analysis using SQL or Python, and data-focused experimentation. Preferred experience includes machine learning model training and evaluation, agentic systems, C++, and large-scale distributed systems. The internship is hybrid and onsite.

Build scalable machine learning pipelines, data and training infrastructure, distributed processing workflows, and reusable software systems for foundation-model research. Own codebase health, testing, reliability, maintainability, and performance across ML workflows. Collaborate with researchers and engineers to translate model and experiment requirements into robust systems supporting large datasets, large models, multimodal data, video, robotics, and embodied AI.

Develop autonomy algorithms that extract semantic meaning from urban driving data, architect onboard systems, optimize evaluation datasets, and deploy machine learning techniques into production. The role involves managing sensor dependencies, defining performance metrics, identifying complex edge cases, and collaborating with platform, product, and security engineering teams to support autonomous vehicle data and safety-critical systems.

Develop autonomy algorithms that extract semantic meaning from complex driving scenarios and enrich Uber’s autonomous vehicle data lake. Design onboard systems, manage sensor dependencies, define evaluation datasets and metrics, and deploy machine learning techniques into production. Collaborate with platform, product, and security engineering teams. The role focuses on physical AI, deep scene understanding, causal modeling, and robust solutions for safety-critical autonomous driving systems.

Develop autonomy algorithms that extract semantic meaning from complex urban driving scenarios and enrich AV data. Design onboard systems, manage sensor dependencies, define evaluation datasets and metrics, and collaborate with platform, product, and security engineering teams to deploy machine learning techniques into production.

Builds end-to-end AI Copilot experiences across voice, vision, text, and action. Owns features from concept through scalable production, collaborates with applied AI researchers, rapidly ships experiments, analyzes usage, and iterates on products used by millions. The role requires full-stack frontend and backend expertise, scalable web API development, strong Python skills, and comfort working in ambiguous, fast-moving environments.

Designs, develops, tests, troubleshoots, and enhances large-scale distributed systems software. The role involves building networking, database, utility, and internet-related subsystems; integrating microservices and AI/ML services; debugging code; and creating testing documentation. The engineer leads project teams, collaborates with internal and outsourced development partners, communicates project progress, and mentors less-experienced engineers.

Leads the design and implementation of scalable full-stack software and algorithms for intelligent agricultural robots. Improves system architecture, performance, latency, reliability, and chemical application accuracy. Develops real-time C++ software for Linux, robotics communication systems, vehicle software, and testing solutions. Mentors engineers, leads cross-functional collaboration, and supports field testing, data collection, research, and customer deployments.

Contribute to development of infrastructure management platform for distributed cloud resources. Build monitoring, automated network configuration, IP allocation and routing systems. Work on cloud, containerization, networking, and high-performance computing projects while learning and growing engineering skills.

Owns end-to-end evaluation and validation processes for autonomous vehicle software and end-to-end machine learning stacks. Designs scalable metrics, ELT infrastructure, automated triage strategies, and KPI monitoring using simulation and on-road data. Performs root-cause and behavioral analysis, communicates data-driven recommendations, and connects continuous improvement efforts to product safety cases and compliance standards. Collaborates with AI/ML, simulation, systems engineering, and product teams.

Develop and maintain scalable build, regression, and release infrastructure for chip designers. Build user-facing services for scheduling, tracking, and triaging workflows, along with tools for monitoring and visualizing build and deployment metrics. Apply CI/CD practices, maintain reliable tooling, and support evolving chip design architectures. The role requires production-quality software development using compiled and scripting languages, with opportunities to work on AI/ML, distributed systems, build systems, and full-stack development.

Leads the design and development of a highly distributed edge computing platform using Go, Kubernetes, microservices, and cloud technologies. Responsibilities include building scalable and fault-tolerant systems, designing APIs, conducting code reviews, troubleshooting complex distributed software issues, optimizing performance and security, collaborating cross-functionally, mentoring engineers, planning projects, and maintaining technical documentation.

Design and operate Bazel-centric build and release infrastructure spanning embedded firmware, cloud microservices, and gateway controllers. Build hermetic, reproducible pipelines; manage cross-compilation toolchains, monorepos, containerized CI/CD, Kubernetes deployments, hardware-in-the-loop testing, and secure OTA releases. Ensure reliable source-to-production delivery across satellite, terminal, and cloud systems.

Own Uber’s Android build platform across Bazel, Starlark rules, toolchains, dependency management, remote caching, remote execution, and CI. Improve build speed, reliability, cost, diagnostics, and test selection across a large monorepo. Lead platform migrations, upgrades, observability, incident response, technical standards, and cross-team initiatives while mentoring engineers and setting the Android build roadmap.

Develop autonomy algorithms for semantic understanding, data mining, scene interpretation, and causal modeling of autonomous vehicle behavior. Architect onboard systems, manage sensor dependencies, define evaluation metrics, and deploy scalable, safety-critical solutions. Collaborate with platform, product, and security engineering teams to bring autonomous driving systems into production.

Design, develop, debug, and support user-space software for enterprise hardware platforms and software-defined data centers. Work across storage, networking, operating systems, distributed systems, hardware bring-up, system validation, manufacturing release, customer deployment, upgrades, and fleet reliability. Build tools and automation in C, C++, Python, Go, and Rust; improve remote management, RAS, observability, and diagnostics. Partner with hardware, systems, OS, customers, and technology teams while leading cross-functional technical initiatives.