Software Engineer Jobs in Sunnyvale, CA

Design, build, and maintain scalable data processing pipelines and infrastructure (ETL/ELT). Implement large-scale data processing (Spark, MapReduce, Kafka), support stakeholders with analysis and reporting, ensure secure multi-region data handling, and optimize data delivery for analytics and business insights.

Lead design and implement a scalable chassis automation tool that translates SoC architecture requirements into generated RTL, registers, verification collateral, and integration artifacts. Collaborate with architecture, RTL, verification, and integration teams, enable PPA analysis, integrate with front-end/back-end flows, and mentor junior engineers to deliver high-quality automated outputs.

Design and build safe, auditable agent and autoresearch infrastructure: closed-loop evaluation, isolation and permissioning, experiment orchestration, and large-scale inference/training pipelines. Enable autonomous research loops, evaluator and confidence machinery, and agent runtime features (orchestration, sandboxing, tool frameworks, memory, retrieval). Work end-to-end with engineers to deploy trustworthy LLM-agent capabilities against production systems.

Lead design and development of diagnostics and validation systems for NVIDIA data center server platforms. Drive platform bring-up, hardware validation strategies, root-cause analysis, and diagnostic software across ODMs, CSPs, and field operations. Provide technical leadership, mentor teams, and define diagnostic architecture and roadmaps to ensure reliability and performance at scale.

Build and operate large-scale ML training infrastructure: distributed GPU training, multi-cluster scheduling, data pipelines (batch and streaming), ML workflows, observability, reliability, and on-call incident response to keep autonomy model training running efficiently.

Build and maintain core ML infrastructure: design and implement ML training, optimization, validation, and deployment pipelines; operate an in-house ML inference and compiler platform; implement testing, monitoring, and observability for model lifecycles; collaborate with cross-functional teams to deploy optimized models to vehicle hardware.

Develop and maintain embedded software for SDV solutions, focusing on high-performance platforms, safety-critical software, and RTOS integration with hardware.

The Staff Software Engineer will design, develop, and optimize large-scale cloud software systems, focusing on user-centric solutions and performance. Responsibilities include system architecture, hands-on coding, and cross-functional collaboration, leveraging modern software practices and technologies.

The role involves owning and maintaining HD maps infrastructure, defining storage formats, and collaborating with engineers and customers to enhance map-related features.

Build and maintain full‑stack web applications and APIs for data and simulation platforms. Design relational data models, backend Python services, async jobs, and React/TypeScript frontends. Implement tooling for scenario authoring, large-scale simulation runs, results browsing, and shared platform foundations (auth, access control, multi‑tenancy). Ensure production reliability, deployment, testing, observability, and compliance with the company Quality Management System.

Design and scale simulation infrastructure and AI agentic workflows to analyze large-scale simulation results, improve simulation-to-reality fidelity, and validate autonomous vehicle systems. Architect pipelines, metrics, and evaluation frameworks; collaborate with cross-disciplinary teams to reproduce and resolve real-world issues and ensure quality and regulatory compliance.

Design and develop scalable front-end and back-end web applications, system infrastructure, and databases. Write clean, unit-tested code, implement CI/CD, cloud and integration solutions, and collaborate with cross-functional teams to deliver high-quality software. Hybrid role requiring local office presence three days per week.

As a Full-Stack Software Engineer, you will build end-to-end features, develop backend services, and create frontend applications while using AI-assisted tools and collaborating with teams.

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.