Software Engineer Jobs in Sunnyvale, CA

Design, build, and operate scalable cloud platform services for deploying, monitoring, governing, and managing AI models and workloads. Lead architecture, reliability, security, observability, automation, and developer self-service initiatives using distributed systems and SRE practices. Collaborate across engineering, product, and research teams, analyze production performance, drive continuous improvement, and mentor engineers while influencing technical strategy.

Develop, integrate, test, and deploy safety- and mission-critical embedded and flight software for aerospace and defense systems. Responsibilities include C/C++ development, digital simulation, integration and testing, full software lifecycle execution, software analysis, and collaboration with engineering and deployment teams. The role requires onsite work in Sunnyvale, an active Secret clearance, and experience with embedded flight software, GitLab, Linux, Windows, and development tools.

Design, evaluate, and deploy machine learning policies for autonomous vehicle interactions, including yielding, lane changes, merges, and cut-ins. Integrate learned models into closed-loop simulation, evaluate safety metrics, and transition models into production. Collaborate across prediction and planning teams while replacing rule-based heuristics with scalable, data-driven solutions. The role requires strong C++ software engineering, machine learning expertise, autonomous systems experience, and cross-functional collaboration.

Design and build a greenfield product that reasons over large-scale data with agentic, LLM-backed systems. Architect high-throughput distributed systems, take AI prototypes to production, ensure reliability, cost and correctness, design safety guardrails for autonomous reasoning, and set engineering standards for quality, testing, and observability.

The Software Engineer will develop and enhance enterprise software products, collaborate with cross-functional teams, and resolve client integration issues.

The Software Engineer will design and enhance software products for Financial Services, collaborate with teams, and resolve technical issues.

Develop Linux kernel and user-space power and thermal management software for NVIDIA Tegra and embedded platforms. Optimize performance, efficiency, latency, compute and memory utilization for edge AI and robotics workloads. Collaborate with hardware, software, and power architecture teams on platform estimation and optimization. Requires strong C, Linux, embedded systems, ARM, and system-level debugging experience.

Design, implement, and operate large-scale observability and telemetry platforms focused on performance, reliability, monitoring, logging, and alerting. Manage services throughout their lifecycle, including system design, deployment, capacity planning, automation, incident response, and postmortems. Build infrastructure tools and frameworks for private and public cloud systems, improve availability and latency, and participate in on-call support for production environments.

Join the Inference team to implement features and improvements for model serving on a GPU platform, focusing on performance and reliability.

Deploys, integrates, and operationalizes vehicle intelligence products for customers in complex environments. Combines software engineering, operating system configuration, system deployment, hardware integration, and customer engagement. Designs scalable architectures, bridges customer systems with Applied Intuition solutions, collaborates across engineering and product teams, and owns technical outcomes through project completion while adapting to changing requirements.

Build and maintain AI-driven workflows, agentic systems, automated operations tooling, cloud infrastructure, and CI/CD pipelines. Handle monitoring, incident triage, backend production issues, and field-operations support. Contribute across the full stack, communicate technical decisions to non-engineering stakeholders, and improve manual processes through automation. Required capabilities include cloud infrastructure, LLM and MCP development, Linux, CI/CD, full-stack engineering, and strong communication.

Build and own an internal manufacturing data platform, including a web portal, REST API, databases, automated pipelines, dashboards, data validation, traceability, cost and inventory tools, and reporting. Collaborate with engineering, test, operations, and supply-chain teams across sites; administer access, security, backups, and documentation; train users and drive adoption.

Develop and optimize GPU-accelerated deep learning inference software for LLMs, multimodal, and generative AI models. Contribute features to vLLM, SGLang, FlashInfer, and NVIDIA inference libraries; implement algorithms, tune performance across GPU architectures, and improve large-scale model serving. The role requires strong C/C++ software engineering, collaboration across framework teams, and expertise in profiling, debugging, performance modeling, GPU programming, or multi-GPU communication.

Define the technical vision and architecture for AI-native cybersecurity solutions using LLMs, agentic AI, retrieval systems, and modern machine learning. Lead scalable distributed-system design, establish engineering standards, partner with product and security stakeholders, and connect innovation to customer outcomes. Champion AI-native development practices, represent technical strategy to executives and customers, mentor senior engineers, and lead cross-functional initiatives without direct authority.

Build and operate ingestion, reconciliation, and reporting systems that reconcile card-network and partner settlement files against internal transactions. Deliver end-to-end features for traceability, accounting journals, tax and regulatory reporting, and compliance tooling while ensuring reliability, scalability, and data privacy.

Design and implement robotic manufacturing applications, including automation sequences, state machines, hardware APIs, failure recovery, calibration, diagnostics, and simulation tools. Optimize machine cycle times, bring up electromechanical hardware, debug across software and hardware boundaries, improve observability and reliability, and participate in an on-call rotation. Daily development is primarily in Python, with collaboration across mechanical, electrical, and process engineering teams.

Own and scale NewsBreak’s advertising platform, including real-time bidding, auctions, advertiser campaign management, DSP integrations, pacing, billing, attribution, and revenue reliability. Build high-QPS, low-latency distributed services, integrate external exchanges, improve auction yield, enforce ad quality, and lead systems from problem definition through production. Collaborate with product, modeling, SRE, and ad operations while improving operational resilience and ownership across critical subsystems.

Develop high-performance AI kernels and software for neuromorphic hardware. Optimize convolutional, transformer, and generative AI workloads using parallelism, sparsity, quantization, fusion, and related techniques. Build performance, power, and area models, reference implementations, benchmarks, validation tools, and regression infrastructure. Collaborate with hardware, compiler, runtime, and application engineers throughout the hardware-software lifecycle.

Designs and operates secure AI applications and backend microservices on AWS. Responsibilities include threat modeling, secure design reviews, vulnerability remediation, secure API development, AI guardrails, prompt testing, RAG pipelines, monitoring, audit logging, and incident readiness. The role collaborates with engineering, product, cloud infrastructure, and security teams to embed secure-by-design practices throughout the software development lifecycle.

Develop internal applications, infrastructure, and tools supporting automated aircraft engineering, certification, requirements management, architecture modeling, and flight-test data analysis. Own the full software lifecycle from planning and coding through deployment, collaborate with product owners and end users, and improve engineering workflows using full-stack web technologies, databases, cloud infrastructure, telemetry pipelines, and data visualization tools.

Develop statistical and machine learning techniques, quantitative models, and scalable automation for evaluation pipelines. Build data-processing infrastructure, improve evaluation efficiency, and solve ambiguous problems across statistics, ML, and large-scale systems. Collaborate with engineers, data scientists, product managers, and leadership while maintaining code quality in a complex codebase.

Set the technical vision and multi-year architecture for hyperscale build infrastructure. Lead build-system migrations, improve C/C++ build speed and reliability, establish reproducible containerized environments, operate CI and build tooling, define engineering metrics, influence organization-wide standards, and mentor engineers.

Design and develop high-performance dataplane software for the TeraWave satellite communications network. Responsibilities include C/C++ packet processing with DPDK and VPP, line-rate optimization at 100G/400G, routing and tunneling integration, hardware accelerator interfaces, distributed dataplane architecture, benchmarking, code reviews, technical leadership, and cross-functional collaboration.

Design and lead cloud and in-car data mining strategies for autonomous vehicle perception and end-to-end models. Build AI-driven software to accelerate data mining, collection, delivery, and corner-case resolution. Develop operational processes using big data, statistics, and machine learning to ensure high-quality training data from production and collection vehicles. Collaborate with platform teams and balance cost, engineering quality, and delivery timelines.

Develop and scale production AI infrastructure supporting large GPU clusters and workloads. Responsibilities include Kubernetes operator and API development, GPU resource scheduling, cluster operations, node health monitoring, telemetry-based reliability improvements, incident analysis, and distributed systems engineering. The role collaborates across teams to improve the performance, availability, and scalability of NVIDIA’s DGX Cloud platform.