Software Engineer Jobs in Sunnyvale, CA

Design and own geometric map-generation algorithms that process large-scale lidar datasets into automated 3D maps for autonomous vehicles. Responsibilities include sensor optimization, pose-graph optimization, multimodal alignment, pipeline scalability, failure-mode analysis, algorithmic debugging, data-quality improvement, and integration with neighboring teams. The role requires strong C++ development, 3D geometry, point-cloud processing, linear algebra, numerical optimization, and probability expertise.

Develop software for data storage and management systems, contributing across the software development lifecycle from design through testing. Work on data efficiency, deduplication, reclamation, replication, performance, scalability, and reliability. Collaborate with senior engineers and cross-functional teams while writing efficient C++ code and maintaining automated test coverage. This primarily in-office role is based in Santa Clara, California.

Software Engineer Interns will own projects from requirements and technical design through implementation, testing, and delivery. They will develop features, optimizations, and infrastructure tools for a data storage and cloud platform; write unit and integration tests; participate in design discussions and code reviews; and collaborate with mentors and cross-functional teams. This is an in-office role based in Santa Clara, California, requiring full-time availability for 12 consecutive weeks during Summer 2027.

Design and operate distributed userspace infrastructure for long-running engineering workflows on bare-metal Linux. Build coordination over NFS, orchestration around IBM LSF, reliability and performance tooling, and incremental modernization from legacy languages such as Perl to Go. The role involves managing concurrency, retries, observability, staged rollouts, and production systems at scale while collaborating with engineers to create durable workflow platforms.

Lead and grow the Admin Console engineering team while owning architecture and execution for enterprise workflows involving data sources, security, deployment, governance, permissions, and AI configuration. Partner with Product, Design, infrastructure, backend, connector, and security teams to simplify complex workflows, improve self-serve activation, increase deployment visibility, and build scalable control-plane capabilities for Glean customers.

Lead architecture and hands-on development of reusable customer-facing AI platform services, including conversational AI, agent orchestration, retrieval, grounding, memory, tool integration, and policy enforcement. Define APIs, data models, deployment designs, testing, evaluation, and operational requirements. Build production systems across GCP and Azure while driving reliability, security, observability, CI/CD, and technical standards. Provide staff-level influence through architecture reviews, mentoring, code reviews, and cross-functional leadership without direct reports.

Build and operate database and storage platform software, including services, APIs, developer tools, migrations, and lifecycle automation. Solve database scaling, performance, reliability, and availability problems across distributed systems, cloud infrastructure, and backend services. Partner with engineering teams on schemas and queries, lead technical projects, modernize platforms, participate in incident response, and use AI-assisted tools in development.

Build and operate database and storage platform software, including services, APIs, and developer tools for provisioning, migrations, upgrades, and lifecycle management. Solve scaling, performance, reliability, and data correctness challenges across databases, distributed systems, cloud infrastructure, and networking. Partner with engineering teams on schemas and platform adoption, lead technical projects through rollout, participate in on-call response, and use AI-assisted tools in development.

Build and deploy AI-powered solutions for clients by scoping ambiguous problems, designing LLM workflows, integrating data and retrieval systems, and creating scalable production tooling. Collaborate with technical and non-technical stakeholders, iterate based on operator feedback, optimize workflows, and support customer deployments. The role requires strong Python and software or ML engineering skills, production deployment experience, communication abilities, customer on-call availability, travel as needed, and hybrid office attendance.

Build and operate full-stack applications and AI-facing features for CoreWeave’s internal data platform. Responsibilities include developing TypeScript, React, Next.js, and Python services; designing APIs and relational data models; integrating analytical data platforms; deploying on Kubernetes; and owning production reliability, testing, observability, and on-call support. The role also involves collaborating with non-engineers to define processes, shipping LLM-backed applications, and evaluating AI output quality.

Develop large-scale data pipelines, infrastructure, and tools for generating, analyzing, and evaluating machine learning datasets from autonomous driving logs and simulation data. Build robust data platforms supporting Waymo Driver launch evaluations, collaborate with Data Science and Quantitative Analytics teams, and improve dataset curation, sampling, slicing, accuracy, and completeness.

Develop optimized GPU algorithms and high-performance machine learning solutions for vector search, databases, and data processing. Responsibilities include designing, implementing, benchmarking, debugging, and optimizing C++, CUDA, and Python libraries; developing clustering and visualization algorithms; collaborating cross-functionally; and contributing to open-source projects such as cuML, cuVS, and RAFT.

Build and operate production software, backend services, data pipelines, infrastructure, and workflow automation for autonomous vehicle simulation testing. Automate test creation, execution, validation, monitoring, and maintenance while integrating evaluation systems and partner tools. Lead technical design, code reviews, architecture, and cross-functional execution across autonomy, safety, systems, data, and infrastructure teams. Improve reliability, observability, quality, and scalability of simulation testing through cloud-native engineering and analytics.

Designs and leads scalable cloud applications, virtualization platforms, and automation for embedded software development and co-simulation. Responsibilities include architecting multi-region cloud infrastructure, developing deployment and maintenance automation, integrating regression testing workflows into CI/CD, and supporting cybersecurity, scalability, resiliency, and cost optimization. The role serves as a subject matter expert, leads cross-functional integrations, collaborates with suppliers, and presents technical solutions to leadership and external organizations.

Own the architecture and technical direction of Zocdoc’s Provider Engagement Platform. Design data pipelines, real-time practice intelligence systems, APIs, and ML integrations that power personalization and recommendations. Lead complex cross-team initiatives, make infrastructure decisions, ship production code using C#, React, and AWS, and mentor engineers while promoting strong engineering, testing, and observability practices.

As a Senior Software Developer, you'll lead automation solutions development for testing processes at GM, collaborating across teams. Responsibilities include building Python-based automation frameworks, conducting code reviews, and mentoring team members.

Develop and deliver scalable Software Asset Management software across the full lifecycle. Responsibilities include designing reusable code, implementing features, automating tests, optimizing performance, collaborating with product managers, architects, and quality engineers, and mentoring peers. The role requires expertise in analytical data stores, distributed data pipelines, dashboards, object-oriented programming, front-end frameworks, automated testing, AI-powered workflows, and production readiness.

Lead backend engineering for IAM platform integrations with AWS, GCP, Azure, Box, HashiCorp, and Databricks. Design scalable, reliable connector services, define architecture and technical standards, mentor software engineers, and drive integration roadmap priorities with cross-functional teams and customers. Apply AI/ML models to streamline integration development and work with complex identity, access, and data systems.

Architects and operates enterprise cryptographic security services for a multi-tenant SaaS platform. Responsibilities include certificate lifecycle management, key management, secrets distribution, PKI, Kubernetes deployment, threat modeling, incident response, compliance with FIPS and regulated-environment requirements, and evaluating AI/ML for security applications. The role also mentors engineers, collaborates across product and security teams, and advances post-quantum cryptography readiness.

Design and implement distributed, exabyte-scale S3-compatible object storage for AI workloads. Improve storage reliability, durability, security, observability, throughput, and latency using technologies such as RDMA, GPU Direct Storage, and distributed filesystem protocols. Collaborate with infrastructure, platform, product, and operations teams to deploy and troubleshoot production systems, develop monitoring dashboards, analyze telemetry, and mentor engineers.

Build scalable, interactive enterprise applications and reusable tools, libraries, and frameworks. Develop backend and frontend systems using Java, JavaScript, Python, AI/ML, conversational AI, and large-scale data technologies. Design and deliver new features, improve existing products, enforce coding and testing standards, collaborate with product owners, and mentor colleagues.

Leads the design, development, and operation of highly available, multi-tenant data platform services on Kubernetes, including Postgres, streaming systems, and key-value stores. Defines distributed-systems architecture, failover, disaster recovery, observability, scalability, and SLOs. Builds operators, controllers, automation, and self-service APIs; drives major technical initiatives; partners across engineering; leads reliability efforts; and mentors engineers. The role requires deep hands-on software development and operation of stateful systems at scale.

Build and operate cloud-native data platform components and services from design through production. Lead scoped projects, create technical designs, improve reliability and scalability, write tests and instrumentation, maintain runbooks, and participate in on-call rotations. Develop Kubernetes operators, controllers, automation, and platform services. Collaborate with senior engineers and mentor junior team members through code reviews, design feedback, and pairing.

Develop Rust-based, GPU-accelerated data processing frameworks and agentic retrieval pipelines for multimodal LLM applications. Build systems for dataset indexing, querying, deduplication, filtering, classification, benchmarking, and optimization. Collaborate with AI researchers and cross-functional teams to develop production tools, prototypes, and roadmaps. Apply prompt engineering, fine-tuning, profiling, and micro-optimization while supporting containerized cloud infrastructure, continuous delivery, peer reviews, and Gen-AI productivity products.

Design and develop security frameworks for Aurora’s autonomous vehicle platform and cloud services. Lead vehicle security implementation, architecture reviews, threat modeling, code reviews, security releases, and integration with partner teams and OEMs. Write production-quality C++ and Golang, mentor engineers, translate requirements into products, and apply cryptographic, infrastructure, network, embedded, and hardware security practices.