Top Tech Jobs & Startup Jobs

Lead a team to build and operate DGX Cloud infrastructure, focusing on Kubernetes operations, automation, and reliability. Manage production systems and engineer practices for cloud infrastructure.

The role involves deploying AI networking solutions in data centers, driving architectural decisions, troubleshooting network issues, and collaborating on customer projects for NVIDIA's technology solutions.

Lead end-to-end technical programs for the NVIDIA Marketplace, coordinating engineering, product, operations, and business partners. Drive planning, backlog management, risk and dependency mitigation, governance, release readiness, and post-launch reviews while reporting program health to leadership and improving cross-team execution and metrics.

Lead end-to-end telemetry and cloud infrastructure programs for DGX Cloud. Coordinate telemetry requirements across hardware, firmware, software, and CSPs, ensure operational readiness, drive attestation and fleet health initiatives, mentor TPMs, improve processes with AI automation, and report progress to executive leadership.

Provide technical support to NVIDIA Enterprise customers by triaging and resolving issues, working with engineering on reproductions/logs, applying AI/ML and agentic AI to build support tools and products, documenting interactions and knowledge, and owning cases to resolution (occasional weekend/holiday support).

Design and implement compiler optimizations and infrastructure for deep learning models. Analyze networks, improve performance and memory, define APIs, and collaborate with framework and hardware teams to enable efficient Ahead-of-Time and Just-in-Time execution across GPUs and NPUs.

Lead architecture and delivery of an ML infrastructure efficiency platform across silicon co-design teams. Define platform contracts, onboarding, orchestration, auth, observability, storage/caching, and SLA enforcement. Own production operation, security, reliability, and performance while mentoring engineers and driving cross-team technical decisions.

Design and implement RTL and system-level SoC modules, perform logic synthesis and timing analysis, integrate modules into SOC, collaborate with architects and verification teams, support silicon bring-up, and improve design flows and methodologies to enhance efficiency and chip yield.

This role involves managing software engineering projects for NVIDIA's autonomous vehicle solutions, coordinating teams, and ensuring quality metrics while improving processes.

The job involves developing core libraries for agent-based applications, optimizing performance, and creating tools for scalable deployment of autonomous systems.