Top Tech Jobs & Startup Jobs

Lead architecture, implementation, and operation of highly available enterprise messaging and collaboration platforms (Exchange on-prem/hybrid/Online, SMTP/IMAP, Azure). Manage upgrades, patching, monitoring, security (SPF/DKIM/DMARC, anti-spam), migrations/tenant consolidations, and SaaS collaboration platforms. Provide incident diagnosis, mentor engineers, and drive automation and AI-enabled operational improvements.

Design and research next-generation datacenter networking solutions across ASIC design, algorithms, topologies and systems. Collaborate with internal teams, partners, standards bodies and open-source communities to develop networking technologies that enable accelerated AI data centers.

Serve as a technical advisor for semiconductor customers and EDA developers to GPU-accelerate EDA and manufacturing workflows, apply ML/DL for inspection and yield, analyze architectures for acceleration, deliver trainings/demos, and collaborate with product and engineering teams to deploy scalable AI-enabled solutions.

Design and implement cloud-native data management services (catalog, metadata, dataset/checkpoint lifecycle) for exabyte-scale GPU workloads. Build backend systems on Kubernetes and major cloud providers, collaborate with research and cross-functional teams, document architecture, and drive integration with storage/compute innovations (GPU Direct Storage, DPU).

Lead forecasting, strategy, and technical enablement to grow NVIDIA Compute platform sales in enterprise markets. Drive partner and ISV relationships, publish market insights, influence product roadmaps, and enable global sales teams to accelerate AI adoption across cloud and on‑prem environments.

Lead development of planet-scale mapping systems from crowdsourced fleet data. Design and implement 3D reconstruction, SfM, pose estimation, sensor fusion, map fusion, change-detection, and production C++ pipelines. Build evaluation, visualization, and debugging tools, and collaborate with perception, localization, and planning teams to integrate high-quality maps into autonomous driving systems.

Architect, develop, and debug system software for NVIDIA Halos across QNX, Linux, and hypervisor environments. Build BSP, boot, drivers, I/O virtualization, and platform software for NVIDIA SoCs. Ensure safety and security compliance (ISO 26262/21434), use formal methods, optimize platform performance, and collaborate with ASIC, firmware, OS, safety, and security teams. Employ AI-assisted engineering tools to accelerate development, testing, and documentation.

Design and optimize high-performance C++/CUDA libraries for GPU-based data processing. Improve multi-node GPU communication (UcxExchange), optimize Presto GPU query performance, and lead enhancements across Presto, Velox, and cuDF projects for efficient DataFrame and database acceleration.

Design and implement an MLIR-based AI compiler for GPU inference: develop graph representations and dialects, optimize performance and memory, define APIs, generate kernels, and collaborate with framework and hardware teams to enable new model patterns and GPU features.

The role focuses on optimizing and managing workload scheduling systems for EDA, enhancing observability, service reliability, and automation while resolving performance issues.