Software Engineer Jobs in Santa Clara, CA

Build and improve core libraries, frameworks, and developer tooling to increase engineering velocity. Work on build and CI infrastructure (Bazel, Buildkite), collaborate cross-functionally to improve code quality, testability, and release processes, and define best practices for developer workflows.

Build scalable Python-based tooling and infrastructure for autonomous vehicles, including systems for fleet management and vehicle communication. Design systems supporting multiple vehicle platforms and environments, collaborate across the autonomy stack, and support development, testing, and deployment of autonomy software.

Build and maintain large-scale cloud simulation infrastructure across AWS, GCP, and Azure. Improve deployment reliability, monitor and resolve bottlenecks, optimize CI/CD and developer tooling, and ensure interoperability with customers' autonomy software.

Design and implement scalable, secure Over-the-Air update platforms in C++ and Go. Build cloud-native infrastructure, package management, CDNs/PDNs, secure delivery pipelines (cryptographic signing, encrypted channels), containerized deployment, monitoring and analytics, and support large-scale device fleets across embedded Linux and RTOS devices.

Build scalable telematics backend systems and data pipelines to ingest, process, and analyze high-volume real-time telemetry from millions of devices. Design microservices, cloud storage, D2D communication, and integrate analytics/ML for predictive maintenance and fleet insights. Collaborate cross-functionally to deliver production-grade, high-availability telematics solutions.

Design, implement, and tune locomotion, whole-body control, and manipulation software for bi-dexterous robots. Integrate subsystems across actuators, sensors, and motor controllers, develop real-time C++ control, validate in simulation, debug hardware failures, and contribute to fleet tooling and CI/CD pipelines.

Design and implement lifelong mapping and localization systems for vehicles, build scalable local/global maps, fuse live sensor data with maps, develop real-time onboard and offboard localization, leverage inertial/GNSS/camera/lidar/radar data, and continuously improve performance using large-scale, data-driven methods.

Optimize application-layer software for embedded autonomy platforms by profiling and tuning runtime performance, resolving resource contention, ensuring efficient concurrent execution, and deploying production code on QNX/Linux/RTOS targets while collaborating with ML runtime teams.

Develop and integrate Unreal Engine-based realtime 3D simulation features, bridge the core simulation engine with Unreal, utilize Cesium for large-scale environments, customize plugins and content ingestion, deploy engines on local and cloud platforms, and optimize simulation performance and accuracy.

Design, build, and maintain scalable, low-latency backend services and cloud infrastructure for remote assistance. Implement APIs, data pipelines, protobuf/gRPC communication, NoSQL persistence (Redis), real-time data streaming, and resilience across AWS regions. Collaborate with onboard and frontend teams to ensure secure, reliable end-to-end data flow and optimize serialization and transmission.

Build and maintain a calibration pipeline for multi-sensor vehicles, manage calibration lifecycle and deployment, support offline and online calibration algorithms, enable sensor fusion across cameras, lidar, radar and inertial sensors, collaborate with algorithm teams, and integrate calibration status into HMI for production workflows.

Build and productionize scalable backend services, APIs, and AI workflows to connect requirements, modeling, validation, and test data for autonomous vehicle programs. Implement traceability, versioning, dashboards, and KPIs, refactor prototypes into certifiable systems, and collaborate with systems engineering, safety, and autonomy teams to support compliance and validation at scale.

Build and operate the Insights data and analytics platform: ingestion, reliability, query infrastructure, visualization, dataset lifecycle, governance, transformation, and agentic analytics for physical AI at scale.

Develop high-performance motion planning modules for onroad autonomous vehicles, integrating lightweight maps and perception outputs. Ship production C++ code, deploy to vehicle hardware, test on road, and collaborate with customers to meet diverse operational design domains.

Design, build, and maintain high-quality Android applications integrated with Vehicle OS. Collaborate with product, design, and backend teams to deliver features, optimize performance and stability, conduct code reviews, and contribute to architecture and sprint planning.

Build and ship shared AI infrastructure, agent frameworks, and tooling; partner with product teams to productionize LLM and agentic features; own GenAI best practices for architecture, safety, evaluation, and deployment; develop agentic systems and AI SRE tooling; engage with customers to shape roadmap and demos.

Design, build, and maintain core libraries, frameworks, and developer tools for Android Automotive OS. Own developer infrastructure and Gerrit code review, develop automated and static analysis tooling, collaborate with platform and app teams to improve code quality, build performance, and release workflows, and set tooling best practices.

Design, develop, integrate, and test flight and firmware for satellite systems. Implement application, platform, and driver code for ARM Cortex-M embedded devices (bare-metal/RTOS), collaborate with hardware and software teams, select technologies, and develop hardware-in-the-loop test strategies through on-orbit operations.

Develop and optimize Linux kernel features and device drivers for enterprise storage arrays. Maintain and patch kernel code, diagnose hardware-software boundary issues, optimize performance (NUMA, interrupts, threading, CPU instruction sets), lead architecture and development from concept to release, mentor peers, participate in code reviews, and collaborate with partners and vendors.

Architect and deliver high-performance C/C++ networking software for enterprise storage platforms. Implement Layer 2/3 features, integrate with ASICs and switch SDKs, enable non-disruptive upgrades, customize SONiC, and lead cross-functional hardware-software efforts while mentoring engineers.

Develop and maintain full-stack applications supporting foundation-model research. Design client- and server-side architecture, ensure responsiveness, security, and performance, collaborate with researchers/ML engineers, troubleshoot and document software, and contribute to HPC and deep-learning research outputs and publications.

Design and implement low-level embedded software for x86/ARM platforms in C/C++; collaborate with hardware and software teams to spec, test, and debug vehicle subsystems and sensors (camera, radar, lidar, IMU); work on network devices and time synchronization; perform hands-on hardware bring-up and on-vehicle debugging of buses like I2C, CAN, SPI, UART; ensure reliability and safety for autonomous trucking systems.

Design, develop, and debug system software for NVIDIA Halos across QNX, Linux, and hypervisor environments. Build BSPs, I/O virtualization, drivers, boot and diagnostics for mixed-criticality NVIDIA SoC platforms. Apply formal methods and safety standards (ISO 26262/21434), optimize platform bring-up, and implement debugging, tracing, logging, and performance-analysis solutions. Collaborate with ASIC, firmware, OS, safety, security, and platform teams.

Lead performance and scalability analysis of the Kubernetes-based accelerated runtime stack, design upstream control-plane changes for hyperscale clusters, optimize container startup and inference latency, advance confidential container performance, model large AI-factory deployments with simulations, build at-scale tests and monitoring, and collaborate with researchers and upstream communities to validate and publish results.

Design and implement cloud-native data management services (catalog, metadata, dataset/checkpoint lifecycle) for exabyte-scale GPU workloads. Build backend systems on Kubernetes and major cloud providers, collaborate with research and cross-functional teams, document architecture, and drive integration with storage/compute innovations (GPU Direct Storage, DPU).