Software Engineer Jobs in Sunnyvale, CA

Lead pre-silicon system software bring-up and validation on simulation platforms. Develop automation, tools, and workflows to improve simulation-based development, debug complex cross-stack issues, enable teams to use virtual platforms, and drive platform readiness for new chips in early-development environments.

Lead and execute perception R&D and engineering for factory robots: define multi-year roadmap, architect perception pipelines (detection, segmentation, 6-DoF pose, scene understanding), drive sensor fusion and calibration, establish data/model workflows and deployment practices, integrate with planning/control, hire and mentor engineers, and evaluate research for production adoption.

The role involves designing solutions for autonomy, developing products, and collaborating with experts in various fields while mentoring engineers.

Design and build a proto-driven code-generation pipeline to emit Go SDKs, CLI commands, and Terraform resources. Own API service framework components end-to-end, enforce API standards, collaborate with teams on API design, improve developer experience, and mentor engineers.

Develop and modernize a Windows GUI application: implement a resizable main dialog, responsive controls and fonts, persist settings on exit, ensure HPE-compliant UI elements, and perform additional GUI-related enhancements using WinAPI, MFC, C/C++ in Visual Studio.

As a Machine Learning Engineer, you will develop models for NLP and code-generation systems, analyze data, and improve AI performance using advanced algorithms. You'll manage the entire ML lifecycle and ensure effective communication of model benefits across the organization.

Develop and maintain scalable, reliable back-end systems and APIs, write maintainable code, and collaborate with global teams in a hybrid work environment.

Design and develop user interfaces and backend architectures for web applications, ensuring seamless integration and optimal performance using modern web technologies.

Design, build, and optimize multi-hop data center fabrics for large-scale AI inference. Work across userspace, kernel, drivers, ASIC SDKs, firmware, and optics to tune latency, bandwidth, and reliability. Lead fabric bring-up, telemetry, automation, validation, and operational best practices while mentoring teammates and partnering with hardware, platform, and manufacturing teams.

As a Software Engineering Intern, you will build foundational code and data processing systems, tackling challenges at the intersection of AI, code understanding, and data analytics.

Design and develop complex software solutions for semiconductor equipment, lead projects, define specifications, troubleshoot software problems, and communicate with customers.

Build and lead the inference orchestration layer for a globally distributed ML inference platform. Architect and implement highly available, low-latency systems, own reliability and performance, write production code, drive incident response, observability, capacity planning, and collaborate with ML, infrastructure, and cloud teams on scalable designs.

As a Senior Full Stack Software Engineer at Doxel, you will design and develop applications for project management, focusing on complex data handling and intuitive UI. Your role involves collaborating across teams and providing technical leadership in software projects.

Develop and maintain high-performance automotive infotainment UI applications in modern C++. Design scalable UI architecture, debug rendering and performance issues, integrate vehicle signals, support feature bring-up across QNX/Linux/Android, optimize memory and startup, and collaborate with cross-functional teams through code reviews and CI/CD workflows.

Design, build, and maintain production platforms and services that automate and operate CoreWeave's network (config generation, provisioning, workflow automation, observability, CLIs/APIs). Lead technical direction, plan multi-month projects, write high-quality Python and Go software, define SLOs/SLIs, reduce manual toil, participate in on-call, mentor engineers, and collaborate across Network, Observability, Fleet, and HPC teams.

As an MLOps engineer, you will develop optimized data pipelines, enhance data engine architecture, and integrate foundation models while working closely with DoD customers.

Build backend systems for a marketplace: design architecture, implement calendar inventory, search, payments, and APIs; write tests; collaborate with front-end; automate processes and help grow engineering culture.

Implement and extend Java-based REST services for the Low/No Connectivity project. Build APIs, unit tests, fix defects, participate in design/code reviews and Agile team ceremonies, and coordinate with engineering and product management.

Build node and cluster management for MatX AI systems, including node health, telemetry, REST APIs, CLI tools, cluster failover, firmware/update orchestration, and integrated host/BMC management. Prototype low-level drivers and daemons, debug across API/daemon/kernel/firmware/hardware boundaries, and design tooling for lab bring-up and fleet-scale management.

Design, build, extend, test, deploy, and maintain a centralized CI/CD infrastructure for open-source accelerated computing projects. Collaborate across teams, define CI/CD best practices, debug production issues, support other teams, and mentor junior engineers while setting technical direction and standards.

Design, implement, and harden safety-critical onboard subsystems in modern C++ on embedded Linux for autonomous BVLOS drone missions. Own features end-to-end, drive verification from simulation through flight test, triage field issues, and collaborate with Engineering, Operations, Safety, and Production to deploy and support production fleets.

Design, implement, and maintain TT-Fabric, a low-level high-performance networking library for large-scale AI clusters. Build scalable communication protocols, optimize synchronization and data movement for thousands of processors, integrate APIs with AI and hardware teams, and help define the distributed systems architecture to maximize hardware performance.

The Software Engineer, Platform role involves designing and maintaining backend APIs for various services at Speechify, focusing on performance and scalability while collaborating with cross-functional teams.

The Software Engineer will support data collection for model training, manage the cloud infrastructure, and collaborate on data pipelines to enhance Speechify's AI capabilities.

Design and build AI agents, first-party web and mobile apps, and scalable backend services. Integrate LLM frameworks and enterprise systems, implement APIs and microservices, ensure observability and security, and collaborate with Finance, Security, and Engineering stakeholders.