Top Tech Jobs & Startup Jobs in Austin, TX

Lead technical performance analysis and optimization of large-scale AI/HPC clusters. Diagnose cross-component bottlenecks, build and maintain benchmarking suites, collect and transform telemetry into time-series dashboards, and collaborate with engineering, field teams, and customers to resolve configuration and performance issues.

Develop and improve C++ algorithms and optimization engines for VLSI physical design (sizing, buffering, CTS, legalization, ECO routing). Own discovery through deployment, collaborate with design teams, and optimize for frequency, power, and performance using EDA tools and scripting flows.

Develop and support software tools for chip design and verification, optimize workflows, work collaboratively to create high-performance software.

The Senior Solutions Architect will develop and deploy AI infrastructure solutions, work with customers, and drive technical pre-sales activities.

Drive physical design and timing for high-frequency, low-power CPUs/GPUs/SoCs from RTL to GDS2. Perform synthesis, STA, timing constraint generation, timing convergence, placement/routing optimizations, ECO implementation, DFT closure, and cross-team methodology improvements to achieve timing and power targets.

Verify ASIC SoCs and IP with emphasis on cache coherency across CPU/GPU memory subsystems. Develop UVM/SystemVerilog testbenches, constrained-random and directed tests, create test plans, collaborate across architecture, design, software, emulation and post-silicon teams, and drive silicon/platform verification strategies.

Develop and optimize state-of-the-art deep learning and ML techniques for current and next-generation GPUs. Analyze and tune performance, provide GPU-based AI solutions to customers, and collaborate with architecture, research, libraries, tools, and system software teams to influence future hardware and software designs.

Develop and maintain GPU performance foundation libraries and test frameworks for Nsight tools. Implement GPU assembly tests, use emulators/simulators to validate instruction events, and document data workflows. Collaborate with hardware architecture teams to enable performance analysis and optimization of GPU-accelerated applications.

Lead development and validation of LLM inference platforms for NVIDIA edge GPUs. Track open-source framework innovations, analyze model-to-hardware mapping, optimize GPU kernels and multi-node inference, produce performance reports, maintain developer inference recipes, own model bring-up workflows, and support partners on hardware-specific inference issues.

Review software releases and open-source components for security, licensing, and compliance. Provide first-line license triage, route complex cases to the Open Source Review Board, mentor developers on SDLC and licensing requirements, host office hours, and coordinate with security, engineering, and compliance teams to ensure timely, policy-aligned software delivery.