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Drive adoption of NVIDIA Omniverse and physical AI technologies across software partners. Advise engineering teams on architecture, coding, integrations, and reference solutions; create technical enablement materials; lead workshops and technical engagements; resolve implementation blockers; communicate partner feedback internally; and support product launches and technical go-to-market activities. The role requires extensive software development experience, industrial or robotics technology expertise, and the ability to influence engineers, executives, and product teams.

Lead real and personal property tax compliance, filings, audits, assessments, appeals, forecasting, and reporting. Manage franchise tax, Form 720, and FBAR processes across corporate entities. Use SAP to maintain tax and fixed-asset data, improve processes, and support accurate reporting. Partner with finance, accounting, IT, consultants, assessors, and taxing authorities while monitoring regulatory changes and developing strategies to reduce tax liabilities.

Develop and deploy machine learning models, datasets, algorithms, and training recipes to improve AI safety for multimodal LLMs and agentic systems. Work across LLM security, frontier risks, agentic safety, multi-turn evaluation, content safety, hallucinations, and fairness. Apply post-training methods including SFT and RLHF/RLAIF, conduct safety evaluations and research, and collaborate cross-functionally with engineering, data science, and research teams.

Builds developer and customer relationships across the Jetson ecosystem, guides partners through embedded Linux and Jetson software integration, promotes NVIDIA AI libraries and edge AI capabilities, supports production deployments, and communicates developer feedback to engineering and product teams to shape platform roadmaps, reference designs, positioning, and adoption.

Design and implement GPU compiler components, optimize compiler performance, solve graphics and parallel-computing compilation problems, collaborate with GPU driver and architecture teams, contribute to LLVM and DXC open-source projects, and help define SPIR-V extensions and standards.

Manage procurement, deployment, and lifecycle of lab and data-center infrastructure. Build, configure, monitor, and troubleshoot servers, networking, virtualization, storage, and remote-management systems. Maintain runbooks, asset records, cabling, and operational processes while partnering with engineering, IT, facilities, and network teams to ensure capacity, availability, and site readiness.

Develop and automate compiler verification tests for GPU compute performance. Analyze functional defects and performance regressions, identify root causes, track issues to resolution, and collaborate with compiler developers. Create test plans, implement and integrate test cases, maintain performance baselines, generate reports and statistics, investigate outliers, and improve testing processes. Work includes programming, build and test automation, execution, reporting, and performance trend analysis.

Design, implement, tune, and productize silicon power and thermal controllers for GPUs, CPUs, and SoCs. Lead power-limit debugging, system-level optimization, silicon bring-up, validation, DVFS, modeling, and performance-per-watt improvements. Collaborate across hardware, firmware, software, architecture, manufacturing, and globally distributed engineering teams. Translate power, thermal, and performance data into executive-level decisions regarding product risks, binning, and program impact.

Design and implement production ML algorithms for real-time streaming telemetry at massive scale, optimized for resource-constrained environments. Build end-to-end ML pipelines, collaborate with Data Science to translate research into production, and improve anomaly detection, health scoring, and predictive analytics for GPU and network infrastructure.

Design, build, deploy, and scale distributed cloud systems for NVIDIA GeForce NOW. Develop backend services and microservices, optimize reliability and performance, drive automation, monitoring, and infrastructure improvements, and build scalable test harnesses. Influence architecture and technology choices while collaborating across teams, mentoring engineers, and promoting technical excellence and operational ownership.