Top Tech Jobs & Startup Jobs

Designs, configures, supports, and improves SAP PP, PS, and MM solutions for manufacturing supply chain operations. Partners with business, engineering, finance, development, offshore, and external manufacturing teams to analyze requirements, architect solutions, implement projects, and manage integrations. Leads testing, training, documentation, and process improvements involving inventory, subcontracting, vendor management, stock transfers, batch handling, and mass production. The role also supports SAP upgrades, lifecycle implementations, and semiconductor manufacturing operations.

Lead and grow a technical team responsible for verifying AI compilers for next-generation workloads. Define formal verification requirements, drive AI-assisted and compiler-aware verification (fuzzing, differential testing, symbolic reasoning, formal methods), and partner with compiler, CUDA, runtime, and ML framework teams to build scalable verification infrastructure and improve production confidence.

Leads architecture and operation of NVIDIA’s global compute platform across bare metal, virtualized, and cloud environments. Responsibilities include managing Kubernetes, OpenShift, KubeVirt, large-scale GPU infrastructure, automated remediation, telemetry, capacity planning, infrastructure-as-code, self-service platforms, GitOps, and legacy workload migrations. The role requires influencing autonomous engineering teams, handling hardware failures and large-scale infrastructure constraints, and establishing operational maturity for frontier AI inference systems.

Leads NVIDIA’s global Compute Core Engineering organization, managing talent and defining infrastructure strategy across data centers, cloud environments, and compute platforms. Oversees modernization, automation, reliability, scalability, security, disaster recovery, capacity forecasting, and lifecycle management for Linux and foundational infrastructure services. Drives self-service platforms using Go, Python, Terraform, and GitOps, establishes service health metrics, leads incident reviews, and partners with leadership and internal customers to deliver resilient infrastructure products.

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.

This role involves developing high-performance software for autonomous vehicles, focusing on sensor drivers, data processing, and vehicle interface integration, while adhering to quality standards.

Develop system requirements, performance budgets, test strategies, metrics, and verification processes for L3/L4 autonomous driving products. Analyze safety-critical systems, datasets, and software architectures while coordinating vehicle and component testing. Partner with engineering, safety, validation, analytics, and product teams to ensure functional and safety compliance. Apply SOTIF, ISO 26262, architectural trade-off analysis, and validation strategies for deep learning and modular autonomous-driving systems.

Leads end-to-end development and execution of autonomous driving software features across multiple engineering teams. Defines roadmaps, schedules, release content, quality metrics, and program tracking while resolving technical challenges affecting scope, schedule, and quality. Communicates program status to management and cross-functional teams. Requires strong experience in complex software engineering programs, automotive, robotics, or AI, with leadership across global organizations.

As an EDA Workflow Optimization Engineer, you will optimize and enhance workflows for chip development, working with teams to investigate, debug, and innovate tools for efficient engineering processes.

Design, develop, and bring up embedded software for autonomous vehicle hardware, including cameras, radar, and lidar. Integrate and debug hardware and software across vehicle subsystems, support DRIVE platform customization for customers, improve platform reliability, and resolve complex issues from application through kernel level. Work across Linux, QNX RTOS, hypervisor, and ARM-based SoC environments while collaborating with software, hardware, systems, and customer teams.