Top Tech Jobs & Startup Jobs in Austin, TX

Build and operate massively distributed, scalable GPU cluster platforms (DGX Cloud) to monitor, diagnose, and remediate GPU performance issues. Ensure reliable, high-performance production AI clusters, evaluate failures, improve services via incident management, and collaborate across teams to automate cluster operations and scheduling.

Design and deploy LLM-powered validation pipelines and AI integrations for silicon design toolchains. Collaborate across teams to identify AI opportunities, build productionized agentic workflows, evaluate emerging AI tech, and measure impact with data systems to improve validation, characterization, and automation of chip bring-up and verification.

Build and operate scalable backend services and data platform integrations for customer profiles, consent, personalization, campaign operations, and marketing intelligence. Design APIs, service integrations, and reusable platform capabilities; modernize database and identity systems; ensure reliability with observability, automation, and incident prevention; partner with cross-functional teams to translate business needs into production-ready solutions using AI-assisted engineering responsibly.

The Senior Performance Compiler Engineer will design and implement compiler technology for optimizing AI performance on NVIDIA GPUs, collaborating with teams to enhance efficiency in AI applications.

Lead hardware-software co-design for LLM inference: drive and document architecture, build executable C++ hardware models, optimize performance with good algorithms and parallelism, diagnose cross-team chip and subsystem issues, and automate workflows to improve efficiency.

Primary point-of-contact for a customer, providing on-site and remote HPC, Ethernet, and AI infrastructure support. Troubleshoot Linux systems, networking protocols, and interoperability; reproduce and resolve complex issues; collaborate with engineering, marketing, and support; document support methodologies and improve processes.

Support and grow the RAPIDS DevOps infrastructure: manage hardware, design and maintain container/build processes, develop and publish Python packages, operate CI/CD, observability, security compliance, Linux systems, and collaborate with engineers to implement DevOps best practices.

Lead global go-to-market and co-sell strategies with AI-native ISVs and foundational model providers. Drive joint-selling, co-marketing, pipeline management, sales enablement, and cross-functional coordination with NVIDIA product and account teams to create repeatable partnership GTM motions and measurable revenue outcomes.

Lead and coordinate global software programs for deep learning training and inference frameworks. Drive cross-functional alignment, manage schedules, risks, and dependencies, implement release and open-source processes, define metrics, report status to senior management, and improve program execution across hardware, software, and infrastructure teams.

Define high-level SoC subsystem and I/O architecture for LPU products, translate product requirements into architecture and IP specifications, build and validate functional/architectural models (C++, SystemC, Python), and drive tradeoffs across performance, power, reliability, and security while coordinating with IP, firmware, software, RTL, verification, and post-silicon teams.