Software Engineer Jobs in Santa Clara, CA

Build and scale backend services, real-time streaming pipelines, and data layers for a real-time AI tracking platform. Design stateful stream-processing, low-latency data models across relational, time-series, and caching layers; expose scalable APIs; write tests, monitor production, and optimize performance and serialization for high-frequency telemetry.

The role involves architecting and maintaining Datagrid Pages and Dataset Editor, improving UI efficiency, writing clean code, mentoring juniors, and collaborating with teams.

As an Embedded Software Test Engineer at Wayve, you'll validate onboard software systems through automated testing, working on embedded platforms, debugging issues, and enhancing test coverage.

Design, implement, and optimize foundational CUDA C++ libraries, parallel algorithms, utilities, and runtime abstractions. Own features across design, implementation, testing, profiling, benchmarking, documentation, and maintenance. Collaborate with compiler, Python, and Rust teams, engage with users on performance and correctness, and improve developer productivity through diagnostics, tooling, and CI integration.

Lead the technical direction for production engineering in NVIDIA DGX Cloud, focusing on Kubernetes operations, automation, and reliability for GPU clusters.

Design and build RL post-training infrastructure for AI, optimizing training-inference-rollout on distributed systems while ensuring fault tolerance and scalability.

As a Senior Software Engineer, you will design and develop scalable solutions within Salesforce, focusing on CPQ and Order Management while collaborating with teams and maintaining software development lifecycle processes.

The role involves designing and developing firmware for Compute, Storage, and Custom ASIC platforms, with responsibilities including hardware validation, testing, and automated processes.

Develop and enhance networking systems software (including Junos/Junos Evolved) for Campus & Branch products. Design, code, test, and integrate software for operating systems, networking protocols, and forwarding ASICs; debug issues; collaborate with product, architects, and stakeholders to deliver reliable networking solutions.

The Application Software Engineer will focus on integrating AI technology for autonomous driving, ensuring software functionality on hardware platforms, and collaborating across teams for smooth delivery.

The role involves deploying and optimizing LLMs, designing the ML serving stack, and ensuring high-performance GPU services for production readiness.

Design and develop software for Wi-Fi access points, collaborate with hardware teams, and enhance firmware for new devices while resolving technical issues.

Design, build, and deploy scalable cloud solutions for GeForce NOW. Collaborate on features, optimize systems, mentor team members in automation and infrastructure practices.

The role involves building and modernizing the RTL-to-GDS flow infrastructure for semiconductor design, improving EDA tool automation, and ensuring system resilience while debugging and collaborating with design teams.

Develop embedded real-time systems software for autonomous vehicle safety services. Optimize solutions for performance and compliance while collaborating with multifaceted teams to integrate technologies into NVIDIA's self-driving platform.

The Software Engineer Intern will develop redundancy systems for autonomous trucks, create protocols for embedded systems, and optimize software integration while collaborating with teams to ensure quality and functionality.

The intern will work on integrating ROS2 into the software stack, implementing hybrid middleware, developing performance benchmarks, and conducting field tests for autonomous trucks.

As a Full Stack Software Engineer at Doxel, you will design and develop full-stack applications, collaborating cross-functionally to optimize user experiences and facilitate data processing for construction projects.

You will design, build, and maintain full stack services for global loyalty products, ensuring scalability, reliability, and performance. Collaborate with cross-functional teams to create and integrate AI-enabled features while adhering to high engineering standards.

Lead RISC-V MCU/SoC integration and develop bare-metal and RTOS firmware for PHY/SerDes validation. Drive silicon bring-up, HW/SW debug, firmware-driven test automation, validation coverage, and toolchain/debug infrastructure. Collaborate with RTL, validation, and architecture teams to enable reusable, closed-loop validation frameworks across simulation, FPGA, and silicon.

NVIDIA seeks a Senior Software Engineer to enhance its AI platform using JAX, focusing on performance optimization in deep learning frameworks while collaborating with applied researchers. The role requires strong programming, system design skills, and a proven ability to develop customer-facing solutions.

Lead design and full SDLC delivery for Venmo Android features. Provide technical leadership, mentor engineers, ensure operational excellence, consume GraphQL/REST APIs, write unit and automation tests, and promote engineering best practices across the team.

Design and evaluate AI/ML and DRL model architectures for FPGA-based systems; develop training/inference pipelines, benchmarks, and simulation environments; optimize hardware-aware models for performance, power, latency, and cost; build tooling for statistical and graph-based learning; collaborate with hardware, software, and product teams to define AI-enabled FPGA product directions.

Design, build, and maintain scalable, secure backend platform infrastructure, deployment pipelines, plugin systems, and cross-platform desktop app infrastructure. Implement authentication/authorization, observability, automated testing, and incident response. Engage customers for feedback, document APIs and best practices, and participate in on-call rotations to ensure platform reliability and performance.

Design and implement high-performance Vision AI pipelines and large-scale distributed services for processing video, image, and 3D data across edge and cloud. Build multi-modal perception, use simulation/synthetic data for testing, profile and optimize GPU-accelerated inference, collaborate with research and product teams, drive code quality and reviews, and mentor engineers to productionize vision models at scale.