Software Engineer Jobs in Sunnyvale, CA

Own and develop Arena’s public web surfaces, including the blog, marketing pages, and leaderboard UI. Build with Next.js, React, TypeScript, Sanity CMS, and the company design system. Improve performance, accessibility, SEO, structured data, internationalization, and data visualization. Create CMS models and publishing tools that enable marketing teams to ship independently while collaborating closely with designers, marketers, and engineers.

Lead architecture and development of reliable, scalable distributed storage services for AI/ML. Build and maintain Go applications, containers, bindings, and CLI tools deployed on Kubernetes. Enhance availability, automate deployment and monitoring, and collaborate with research, product, engineering, and customers. Requires ownership of enterprise software throughout its lifecycle, with experience in distributed systems, cloud services, storage interfaces, and large-scale deployments.

The role involves developing and optimizing system software for autonomous driving platforms, integrating sensors, and collaborating across teams.

Design and implement Windows sensor detection and prevention features for the Falcon platform. Research attack techniques, develop user- and kernel-mode detection logic, own features from design through release, apply secure coding and CI/CD practices, troubleshoot customer issues, and collaborate across teams to improve telemetry and protections.

Design and build scalable AI platform capabilities to enable multi-step GenAI workflows, model execution, and integrations. Implement backend services, execution infrastructure, APIs, and observability to support production GenAI experiences across sales and product teams. Collaborate with AI engineers, data scientists, and product partners to turn AI use cases into reliable, extensible platform features.

Design, implement, and test distributed block and file storage services in C across Linux kernel, userspace, host, and DPU environments. Analyze production issues, resolve complex kernel and systems bugs, develop scalable storage solutions, and collaborate with networking teams, architects, and customers. The role involves defining software architecture for highly performant, scalable storage platforms and requires deep expertise in Linux, storage protocols, distributed systems, and operating-system internals.

Lead the design and optimization of software for autonomous driving silicon, focusing on performance and collaboration across teams.

Build and lead the Vehicle Realism Platform for Waymo’s autonomous-driving simulator. Design scalable architectures, improve simulator reliability and reproducibility, bridge vehicle subsystems with simulation infrastructure, and deliver realistic simulation solutions across hardware platforms. Collaborate with robotics, onboard, hardware, evaluation, and simulator teams. The role requires backend development, production monitoring, systems programming, C++, and experience building products in distributed environments.

Design, build, and scale AI-powered tools, agents, automations, and data integrations for communications use cases. Partner with users to prototype, validate, and productionize solutions; implement security, monitoring, and human review; create reusable components, documentation, and evaluation frameworks for safety, grounding, and reliability.

Build software for renewable energy campuses, including high-fidelity simulations, geospatial data pipelines, automated site and electrical design, and energy management systems. Develop real-time controls, SCADA and telemetry integrations, testing infrastructure, and safety systems for islanded solar and storage facilities. Collaborate with power, civil, and external engineering experts to convert domain knowledge into reliable software and accelerate utility-scale site design and deployment.

Design and build large-scale distributed datapath services for secure, identity-aware access across Microsoft Entra. Develop performant networking and security components, integrate AI-driven telemetry and automation, and deliver reliable Zero Trust solutions. Improve testing, observability, and live-site reliability through modern DevOps practices, code reviews, integration tests, and on-call support. Collaborate cross-functionally on secure access and Copilot-related scenarios.

Principal Software Engineer role at Hewlett Packard Enterprise working onsite from an HPE office. The posting provides limited role-specific responsibilities or qualifications, but identifies the position within Engineering and offers an annual California base salary of $172,000–$349,000, plus potential variable incentives and employee benefits.

Design, implement, test, and maintain cross-platform core libraries for CrowdStrike’s security sensor across Windows, Linux, and macOS. Own work from technical design through production validation, lead design reviews, resolve fleet-scale incidents, improve testing and reliability, collaborate across engineering teams, and mentor junior engineers. The role requires strong low-level C and C++ systems experience, cross-platform expertise, sound technical judgment, and occasional travel.

Develop scalable ML infrastructure for autonomous vehicle use cases within Uber AV Labs. Responsibilities include designing multi-region, multi-cloud platforms; customizing Uber’s ML platform; aligning infrastructure and AV teams; executing technical projects from conception through production; and optimizing GPU efficiency. The role requires expertise in CUDA, TensorRT, Kubernetes, Flyte or Airflow, and Ray, along with at least six years of experience and a computer science degree.

Architect, build, deploy, and operate production-grade AI agentic systems and workflows. Responsibilities include backend and full-stack development, agent orchestration, workflow state, retrieval, memory, approvals, failure recovery, data architecture, enterprise integrations, cloud infrastructure, observability, security, and scaling. The role establishes reusable engineering patterns and partners with users to deliver reliable AI products, while addressing production issues involving model behavior, permissions, latency, cost, and consistency.

Defines architecture and technical direction for production ADAS SoC software powering driver-facing HMI experiences. Builds a next-generation driver monitoring system spanning sensors, perception, inference, vehicle interfaces, diagnostics, and HMI. Leads multi-team design, implementation, integration, performance tuning, validation, release, and issue resolution while establishing quality standards and roadmaps. Mentors engineers and influences cross-functional stakeholders on system trade-offs, reliability, safety, security, and maintainability.

Design and build scalable ML infrastructure and backend systems for high-impact marketplace applications. Lead architecture, solve low-latency and high-correctness problems, develop and adopt engineering frameworks, and create production-ready technical roadmaps. Partner with Product, Science, and Operations while mentoring engineers and improving engineering standards. The role requires experience with ML models, foundational models or LLMs, MLOps, Kubernetes, data pipelines, distributed workflows, and large-scale scheduling.

Develop advanced autonomy algorithms for physical AI, including data mining, deep scene understanding, causal modeling of ego-vehicle behavior, and robust identification of complex driving edge cases. Deploy algorithmic solutions for real-world, safety-critical autonomous systems and help establish high technical standards within Uber’s AV Labs team.

Lead the technical direction and delivery of machine learning and autonomy algorithms for AV Labs. Design onboard systems, sensor integrations, evaluation datasets, and performance metrics for semantic scene understanding and autonomous driving data. Mentor senior engineers, lead large-scale projects from conception through production, and coordinate integration across Uber engineering teams. The role requires expertise in Python and Linux, with preferred experience in C++, CUDA, ROS, computer vision, robotics, and machine learning.

Architect and scale high-concurrency backend systems for Uber’s financial products. Lead technical direction, system architecture, code reviews, reliability, testing, and maintainability while partnering with product, design, and business leaders. Build globally scalable, secure financial transaction frameworks and mentor senior engineering teams. The role requires 10+ years of software engineering experience and expertise in Go, Java, or C++.

Develop firmware and low-level drivers for automotive components and autonomous vehicle sensors. Lead custom hardware bring-up, validation, deployment, and hardware-software co-design. Debug complex embedded systems using hardware tools, optimize sensor data pipelines, and ensure timing and network synchronization. Contribute to production lifecycle execution, embedded architecture, code quality, and team mentoring.

Develop autonomy algorithms and foundation models that extract semantic insights from complex driving data. Design scalable machine learning systems, manage sensor dependencies, optimize datasets through data processing and auto-labeling, and deploy models into production. Collaborate with platform, product, and security engineering teams while providing technical leadership. The role requires expertise in Python, Linux, modern ML frameworks, and preferably autonomous driving, safety-critical systems, C++, and high-performance computing.

Lead the technical direction and development of Uber’s real-time marketplace matching optimization systems. Build and productionize machine learning and decision systems using reinforcement learning, deep learning, causal inference, optimization, and control methods. Formulate ambiguous problems, develop behavioral models, create simulation and experimentation frameworks, and deploy scalable online inference systems. Collaborate cross-functionally, lead 0-to-1 initiatives, improve marketplace performance, and mentor engineers.

Design and build scalable ML infrastructure and backend systems for high-impact marketplace applications. Lead architecture, solve complex low-latency and high-correctness problems, drive organization-wide framework adoption, and translate business requirements into technical roadmaps. Mentor engineers, promote engineering excellence, and develop or support ML models, foundational models, and LLMs using modern MLOps practices, Kubernetes, distributed workflows, and large-scale scheduling.

Develop autonomy algorithms that add semantic understanding to real-world driving data. Design onboard systems, manage sensor dependencies, define evaluation metrics, and build scalable production solutions for safety-critical autonomous vehicle systems. Collaborate with platform, product, and security engineering teams to deploy onboard systems.