英伟达Senior Software Containerization Engineer, Enterprise AI Software
任职要求
• 5+ years building production software with a strong focus on containers and Kubernetes. • Strong Python skills building production-grade tooling/services • Experience with Python SDKs and clients for Kubernetes and cloud services • Expert knowledge of Docker/BuildKit, containerd/OCI, image layering, multi-stage builds, and registry workflows. • Deep experience operating workloads on Kubernetes. • Hands-on experience building and running GPU workloads in k8s, including NVIDIA device plugin, MIG, CUDA drivers/runtime, and resource isolation. • Excellent collaboration and communication skills; ability to influence cross-functional design. • A degree in Computer Science, Computer Engineering, or a related field (BS or MS) or equivalent experience. Ways to stand out from the crowd: • Experience implementing or contributing to next‑generation container build systems and frameworks. • Proven track record delivering secure supply chain: SBOM (SPDX/CycloneDX), signing (cosign), scanning, vulnerability management, policy (OPA/Gatekeeper/Kyverno). • Expertise with Helm chart design systems, Operators, and platform APIs serving many teams. • Background in benchmarking and optimizing inference container performance and startup latency at scale. • Prior experience designing multi-tenant, multi-cluster, or edge/air-gapped container delivery. We are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and creative people in the world working for us. If you're creative and autonomous with a real passion for technology, we want to hear from you.
工作职责
• Design, build, and harden containers for NIM runtimes, inference backends; enable reproducible, multi-arch, CUDA-optimized builds. • Develop Python tooling and services for build orchestration, CI/CD integrations, Helm/Operator automation, and test harnesses; enforce quality with typing, linting, and unit/integration tests. • Help design and evolve Kubernetes deployment patterns for NIMs, including GPU scheduling, autoscaling, and multi-cluster rollouts. • Optimize container performance: layer layout, startup time, build caching, runtime memory/IO, network, and GPU utilization; instrument with metrics and tracing. • Evolve the base image strategy, dependency management, and artifact/registry topology. • Collaborate across research, backend, SRE, and product teams to ensure day-0 availability of new models. • Mentor teammates; set high engineering standards for container quality, security, and operability.
• Design, develop, and manage Streaming and Batch pipelines, supporting key functionalities such as large-scale index construction, web page crawling and feature extraction, image processing, and context re-writing. • Optimize continuously a platform to manage, schedule, and monitor hundreds of pipelines. • Optimize continuously a platform to view, track, debug, and operate massive scale Ads Data. • Evaluate and optimize code and design, to maximize performance, minimize complexity. • Mentor junior SDE and solely drive feature development from ground zero.
• Build, maintain, and enhance data ETL pipelines for processing large-scale data with low latency and high throughput to support Copilot operations.• Own data quality initiatives including monitoring, validation, and remediation to ensure integrity across attribution datasets and downstream dashboards.• Implement schema management solutions that enable quick and seamless evolution of attribution data without disrupting consumers.• Develop and maintain infrastructure that supports both batch and real-time attribution requirements.• Collaborate with product managers, marketing analysts, and data scientists to deliver insights for campaign optimization and growth strategies.• Design scalable attribution data architectures that can handle growing data volumes and evolving business needs.• Implement comprehensive monitoring and observability solutions for attribution pipelines, including SLA tracking and automated alerting.
1. Work with product teams and stakeholders to translate business requirements into scalable technical solutions； 2. Conduct technical discussions, and solution presentations in fluent English with external clients and non-technical stakeholders； 3. Design, develop, test, and deploy Java applications using Spring Boot, adhering to coding standards, best practices, and microservices architecture principles； 4. Develop high volume, high performance, low latency and reliable mission-critical applications； 5. Participate in architectural reviews, apply design patterns and object-oriented design principles, and optimize system performance (e.g., SQL tuning, JVM profiling)； 6. Assist in troubleshooting and resolving software defects and issues； 7. Containerize applications using Docker, manage orchestration via Kubernetes, and deploy to cloud platforms (AWS/Aliyun)； 8. Participate in sprint planning, code reviews, and CI/CD pipeline maintenance within Scrum teams.
• Drive reliability engineering initiatives, including infrastructure automation, service monitoring, incident response, and capacity planning. • Leading and participating in technical design discussions across cross functional teams. • Collaborate with application teams to define and enforce architectural best practices, CI/CD standards, and cloud-native patterns. • Diagnose complex production issues through in-depth troubleshooting and implement resilient solutions to prevent recurrence. • Contribute to the development of internal tools that improve observability, system health, and operational transparency. • Analyze and optimize existing systems, providing enhancements and ongoing support as needed. • Stay current with new technologies and proactively recommend improvements to existing cloud architectures and processes. • Develop and maintain server-side logic, data processing, and application workflows. • Mentor junior engineers and promote a culture of knowledge sharing and continuous improvement.