Software Engineer Jobs in Sunnyvale, CA

Lead design and implementation of GPU-accelerated libraries and integrations for Apache Spark. Develop Java/Scala and CUDA/C++ components for I/O and DataFrame operations, enable interoperability with table formats and metastores, contribute to open source projects, collaborate on distributed systems at scale, and optimize cross-platform CUDA/C++ libraries and CI/testing infrastructure.

Lead technical architect for OCI Networking platform services. Drive design and implementation of scalable distributed systems for routing, workload placement, and fleet lifecycle management. Partner across teams, mentor engineers, lead architecture and operational excellence, and own CI/CD and release automation for production-grade cloud infrastructure.

Design, build, and operate production-grade agentic AI services using LLMs, multi-agent workflows, RAG, and vector DBs. Implement prompt engineering, guardrails, model evaluation, secure RESTful backends in Python, and deploy scalable, observable systems on AWS with containerization and monitoring.

Design, architect, and develop manufacturing software and diagnostics for robotic surgical instruments. Build infrastructure to collect and analyze production data, ensure kinematic performance and safety, qualify production software, support production systems, and lead cross-functional projects from inception to launch within a regulated medical-device environment.

Build and ship production web experiences for databricks.com using an AI-native platform. Implement components and page systems, integrate with CMSs, participate in code review, and embed AI tools across the engineering lifecycle to improve discovery, rendering, and deployment.

Own and evolve the real-time runtime and data pipelines for an automotive multi-camera vision stack: task orchestration, IPC, sensor ingestion, deterministic latency, portability across ECUs and datacenter, simulation/replay/test infra, vehicle communications, and safety/security engineering.

Develop and verify CPU SoC boot firmware for pre- and post-silicon platforms. Define and decompose functional and safety requirements, perform failure analysis (FMEA/DFA), implement secure boot features, collaborate across teams, and support silicon validation and productization.

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.

Build and operate Go-based backend services and APIs to manage hardware lifecycle (RMA, data center operations, node repairs). Design scalable, reliable microservices, integrate vendor APIs, manage databases for operational and reporting use cases, and deploy/operate services on container platforms.

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.

Design and develop sensor and compute software for autonomous vehicles: device drivers, inter-device protocols, runtime APIs. Ensure reliability via monitoring, automated testing, debugging, vendor collaboration, and cross-functional project leadership.

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.