Software Engineer Jobs in Santa Clara, CA

The Principal Software Engineer will design and optimize backend services using Rust or Go, debug complex issues, and collaborate on system integrations while adhering to disciplined engineering practices.

The Sr. Staff Software Engineer, Automation will develop tools for automating reliability testing and analysis, collaborating with various teams to optimize workflows and improve product reliability.

As a Senior Staff Software Engineer, you will develop and maintain AI deployment software, optimizing hardware-software co-design, and work closely with various experts to enhance infrastructure.

Responsible for software integration and quality for Cerebras AI platform, focusing on automation, debugging, and cross-team collaboration. Develops QA strategies and testing methodologies to ensure product quality.

Develop and deliver CUDA driver features across pre-silicon simulation, silicon bring-up, and production software. Collaborate with hardware and software teams to design, implement, test, and stabilize GPU compute and graphics functionality across multiple operating systems.

Design and implement high-performance, scalable storage systems and client libraries for AI workloads. Build data loading, checkpointing, caching, POSIX-style and object-store integrations, observability and telemetry, and validate performance with platform, SRE, and AI teams using modern engineering practices.

Develop, debug, and harden kernel-mode GPU and SoC system software across design, emulation, bringup, and production. Focus on performance, power optimization, robustness, and cross-team collaboration for datacenter, desktop, workstation, and console platforms.

Lead development and integration of instrumentation software for digital pathology and robotic systems. Design scalable C#/C++/.NET/Linux applications, develop firmware, implement unit/subsystem/integration tests, collaborate in Agile teams, mentor engineers, prototype new systems, and drive reuse of shared architecture components to deliver high-quality diagnostic products.

Own cloud software and data platform services end to end, including architecture, APIs, data models, pipelines, production operations, monitoring, incident response, and reliability. Build scalable systems for sensor-generated data, use AI-assisted development tools, mentor engineers, and collaborate with product managers to turn ambiguous requirements into production software. The role requires strong backend or full-stack engineering, cloud infrastructure experience, and ownership of systems from prototype through production.

Develop Java-based REST services and APIs for the Low/No Connectivity project. Implement service endpoints, write unit tests, fix defects and enhancements, participate in design/code reviews and Agile team ceremonies, and mentor junior engineers.

Work on an agile team to design and implement an iOS SDK for third-party developers. Develop interfaces, write unit tests, and collaborate with a tech lead, testers, and team members to deliver production-quality SDK components.

Develop and maintain datapath software using C/C++ for high-performance networking on Linux. Work with IP protocols (TCP/UDP), packet routing, drivers, and system configuration. Optional contributions to OpenStack/Neutron plugins, virtualization (VMware/NSX), DPDK or other packet I/O SDKs, and security tools (IDS/IPS, firewalls).

Develop and enhance a retail engagement analytics product by implementing data engineering solutions: build real-time data flows, work with NoSQL stores, support data infrastructure and visualization, clean and prep noisy datasets, and recommend improvements to data reliability, efficiency, and quality.

Implement and enhance Android applications for wearable devices: translate product requirements, design and maintain mobile architecture, add customer-specific features, optimize security, performance and scalability, participate in code reviews, collaborate across teams, and support testing and deployment.

Lead architecture and technical strategy for Cisco's Identity platform: design scalable, secure distributed systems, drive cross‑domain initiatives, influence executives, mentor senior engineers, and represent Cisco externally.

Design, implement and verify boot firmware for flagship CPU SoCs. Define and decompose functional and safety requirements, perform FMEA/DFA, validate on pre-silicon simulation, support silicon bring-up and productization, and collaborate across teams to meet safety and security standards.

Lead development of the application and cognitive layer for humanoid robots: implement behavior trees and intent-to-action orchestration, build voice applications and multi-modal fusion, integrate robotics capabilities and edge/cloud AI services, and ensure production readiness with CI/CD, telemetry, and monitoring.

Design, develop, and execute automated tests for onboard embedded software across OS, middleware, sensors, and integration points. Validate behavior on embedded hardware and HiL setups, debug system-level issues, build reusable test frameworks, integrate tests into CI pipelines, and enable developer self-service testing to improve coverage and speed release cycles.

Design, implement, and optimize AI algorithms and software for computer vision, NLP, recommendation systems and ASR. Develop, test, and maintain models and production-quality code, participate in code reviews and CI/CD workflows, and document algorithms and technical processes.

Design and build machine-learning-driven robotic systems that operate in the real world, support portfolio company growth, influence product and technical direction, and advance company and career outcomes.

As a Software Engineer, you will design, implement, and optimize software solutions, collaborate with teams, and support various stages of development while shaping company culture.

Build scalable, resilient agentic AI and LLM/ML solutions. Translate requirements into high-level and detailed architectures. Implement solutions using Python/C++ and ML frameworks, applying AI/ML fundamentals, data structures, algorithms, and distributed systems.

Design behavioral specs, harnesses, and validation systems so AI agents implement reliable full-stack features. Build CI gates, structural tests, linting, knowledge bases, and end-to-end verification. Diagnose failures across spec, harness, and agent layers. Architect and operate production systems across cloud and on-prem environments for regulated energy deployments, prioritizing reliability, observability, and graceful degradation.

Develop core backend components for a blockchain network, focusing on networking, reliability, scalability, and high-quality software practices.

Develop and automate configuration for distributed clusters, create monitoring tools, manage cloud operations, and ensure system reliability for Cerebras AI supercomputers.