Software Engineer Jobs in San Jose, CA

Develop and optimize an ultra-low-latency media streaming stack for GeForce NOW. Own end-to-end feature development, build tools for video performance and quality analysis, define metrics, analyze CPU/GPU utilization, improve network resilience, participate in design/code reviews, and advance team processes to meet performance, reliability, and scalability goals.

As a Software Engineer, you'll design, develop, and debug software solutions for semiconductor equipment, leading technical initiatives and collaborating with cross-functional teams.

The Software Engineer will design and build systems for sharded PostgreSQL, collaborate with a team to solve distributed systems challenges, and directly engage with customers to create technical solutions.

As a Software Engineer on the Insights team, you'll develop observability products and enhance database performance monitoring for clients using Vitess, MySQL, and PostgreSQL.

As a Senior Full-Stack Software Engineer, you will design, build, and ship AI-powered systems to optimize workflows in the single family rental market, focusing on backend services and full-stack development in a fast-paced environment.

The role involves designing and developing VLSI CAD software, collaborating in agile practices, and advancing design tools for chip development.

The Software Engineer Intern will design, develop, and deploy backend services and APIs, participate in software development activities, write clean code, and troubleshoot issues.

Develop and optimize algorithms and high-performance C/C++ software for physical synthesis, placement, and routing within Cadence Innovus. Contribute to timing, power, and optimization flows, analyze performance bottlenecks, debug and enhance platform features, and collaborate with cross-functional teams to deliver scalable semiconductor design solutions.

The R&D Software Engineer will develop and support mainframe database solutions, focusing on code quality, Agile processes, and customer interaction.

Develop and optimize core infrastructure for autonomous driving. Focus on low-latency execution, component health monitoring, and system performance improvements.

Design and implement RDMA protocol features, QoS and congestion control for high-performance Ethernet NICs. Collaborate with architects, silicon teams, QA, and customer support to deliver, validate, and document high-performance drivers, firmware, and test solutions.

Develop and own software components for ground and space systems; design, implement, test, and monitor code; perform analysis; learn new technologies quickly; communicate clearly and deliver work on time.

Develop and maintain in-house simulation services, integrate numerical models with production software, collaborate with domain experts and stakeholders, apply simulation tools to testing, and contribute to planning and performance metrics.

Build and maintain high-throughput C++ recording systems and Python data services for vehicle sensor and telemetry data. Work on data transfer, ingestion, validation, format/versioning, indexing, compression, and efficient access for replay, analytics, and ML while operating under vehicle resource constraints and contributing to quality management.

Lead architecture and implementation across the full stack, rework user and license management, and develop core runtime components for a code-first PCB design product. Drive technical direction, identify and fix technical debt, mentor engineers, perform code reviews, and build production-ready, high-performance systems involving computational geometry and advanced visualization.

Design, develop, and optimize system software and firmware for SoC-based O-RAN infrastructure. Implement power-management policies (DVFS, clock/power gating, thermal control), analyze RU/DU workloads, build performance and power models, create measurement and test tooling, validate on simulation/emulation and silicon, and influence SoC and platform architectures for 5G/6G deployments.

Lead architecture and execution of platform infrastructure for GPU firmware: set technical direction, design cross-team infrastructure, own reliability (SLIs/SLOs, observability, MTTR), automate pipelines and incident response, build AI-powered workflows, mentor engineers, and drive CI/CD, build, test, and release systems at scale.

Design and implement CUDA/C++ libraries to accelerate Apache Spark DataFrame and I/O operations, collaborate on distributed multi-node GPU solutions, contribute to open-source projects (RAPIDS, CCCL, UCX), and drive testing, CI, and cross-platform optimization for enterprise deployments.

The Software Development Engineer in Test will design automated tests using AI technologies for NVIDIA products, develop testing tools, and collaborate across teams to improve software quality.

Build and operate production Kubernetes-based compute platform for large-scale data and ML workloads. Improve cluster reliability, GitOps delivery, multi-tenant scheduling, resource isolation, GPU workload orchestration, and reusable batch/workflow systems for petabyte-scale processing while contributing to QMS and continuous improvement.

Build scalable, resilient backend microservices in Go; design gRPC/REST APIs; containerize with Docker; deploy and manage services on Kubernetes; implement asynchronous messaging (NATS/RabbitMQ); work with PostgreSQL; drive CI/CD, testing, code reviews, and documentation for greenfield robotics orchestration systems.

Build and productionize AI applications integrating LLMs and vision models into an edge-to-cloud robotics platform. Fine-tune and quantize models, deploy to NVIDIA Orin/Jetson and cloud GPUs, integrate Vector DBs/RAG/agent frameworks, and create data pipelines to collect and version sensor data for retraining.

Build and ship full‑stack product features for a browser-based CAD application: own front-end architecture and UX, maintain backend services (APIs, Postgres on GCP), write well-tested high-performance code (including C++ core), and lead customer-facing technical engagements to turn feedback into product improvements.

Design, implement, and evaluate machine learning and deep learning algorithms—especially ASR for live captioning—using C++ and Python. Build and optimize Conformer, RNN-T, Transformer encoder, and beam-search based systems, perform distributed GPU training, testing, debugging, and documentation. Work with large-scale computing frameworks and adapt ML technologies to VR/AR, robotics, and interactive products. Resolve complex problems, define methods for new assignments, and may coordinate other personnel.

Design and develop Zoom Contact Center features using Java and Spring Boot. Build secure, scalable microservices and RESTful APIs on AWS (EC2, ECS, ElastiCache, S3) with NoSQL. Translate roadmap into specifications, implement integrations, and drive cloud-based test automation and deployment strategies to ensure performance and stability.