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What You’ll Be Doing:

Lead the product strategy and execution for NVIDIA’s Omniverse Digital Twin platform focused on Digital Twin robotics and automation integration use cases. Drive cross-functional alignment and deliver features that enable scalable, Physical AI-powered simulation solutions.

• Define and manage roadmap, use cases, and user journeys for industrial digital twins

• Translate customer needs into clear, prioritized requirements

• Partner with engineering to drive execution and technical trade-offs

• Serve as a voice of the customer across development and GTM teams

• Mentor and guide junior PMs to grow product leadership capacity

• POR & One-page summaries of strategic intent

• Product roadmap with quarterly milestones and long-term vision

• PRDs with use cases, personas, and workflows

• Capability and release launch plans in coordination with GTM and engineering

What We Need To See:

• 7+ years in product management, including experience owning sophisticated platform or developer-facing products.

• BS or MS in Computer Science, Engineering, or equivalent experience.

• Confident navigating cross-functional leadership and high-stakes decision-making, with the ability to lead product initiatives and drive alignment.

• Background in robotics, automation, simulation, or digital twins — or a proven track record to ramp up quickly in highly technical domains.

• A strategic and systems thinker, equally comfortable defining big-picture vision and execution details.

• Experience in both startup and large enterprise settings; adaptable, pragmatic, and process-aware.

Ways To Stand Out From The Crowd:

• Strong sense of purpose and ownership, with an ability to prioritize, deliver product, and encourage those around you.

• Humble, collaborative, and curious, always seeking new ways to tackle problems and empower your team.

What you'll be doing:

• Work with architects, designers, and performance engineers to develop an energy-efficient GPU.

• Identify key design features and workloads for building Machine Learning based unit power/energy models.

• Develop and own methodologies and workflows to train models using ML and/or statistical techniques.

• Improve the accuracy of trained models by using different model representations, objective functions, and learning algorithms.

• Develop methodologies to estimate data movement power/energy accurately.

• Correlate the predicted energy from models built at different stages of the design cycle, with the goal of bridging early estimates to silicon.

• Work with performance infrastructure teams to integrate power/energy models into their platforms to enable combined reporting of performance and power for various workloads.

• Develop tools to debug energy inefficiencies observed in various workloads run on silicon, RTL, and architectural simulators. Identify and suggest solutions to fix the energy inefficiencies.

• Prototype new architectural features, build an energy model for those new features, and analyze the system impact.

• Identify, suggest, and/or participate in studies for improving GPU perf/watt.

What we need to see:

• Pursuing or recently completed a MS or PhD in Electrical Engineering, Computer Engineering, Computer Scienceor equivalent experience.

• Strong coding skills, preferably in Python, C++.

• Background in machine learning, AI, and/or statistical modeling.

• Background in computer architecture and interest in energy-efficient GPU designs.

• Familiarity with Verilog and ASIC design principles is a plus.

• Ability to formulate and analyze algorithms, and comment on their runtime and memory complexities.

• Basic understanding of fundamental concepts of energy consumption, estimation, and low power design.

• Desire to bring quantitative decision-making and analytics to improve the energy efficiency of our products.

• Good verbal/written communication and interpersonal skills.

Collaborating with your peers across various engineering groups, you will optimally launch new systems for NVIDIA HGX GPU Accelerated Server Platforms to production. These purpose-built systems are optimized for the growing Deep Learning, Artificial Intelligence, and Analytics environments. With world-class technology enablingnever-been-seen-beforeperformance levels, NVIDIA’s HGX portfolio is arguably the most complicated systems platform ever developed by humans. This product family represents the company’s fastest growing line of business as well as its largest total available market opportunity. You will bring to bear your knowledge of system architectures and GPU technology in order to productize new GPU boards for datacenter architectures with GPU-accelerated clusters. Your responsibilities will include planning and establishing processes, defining test requirements and optimizing the production line to deliver new GPU boards. You will also be instrumental in helping the team to achieve the desired cost and quality metrics considered outstanding.

This position will be based out of Dallas, Texas.

What you will be doing:

• Use your in-depth experience with high speed networks and signals to plan and develop new diagnostic tests and debug procedures for next gen products

• Use your knowledge of system power-up and handshakes during boot to debug complex interactions between HW, FW and SW on faulty boards

• Recommend, drive and ensure compliance to DFx requirements for robust signal integrity performance as related to layout, mechanical components, assembly procedures, etc.

• Develop and deliver test specs for system level manufacturing screens for all new products to meet the required HW coverage, quality and product requirements.

• We collaborate with CM to define product assembly line, number of test stations and number of assembly fixtures, optimized for cost and efficiency.

• Craft creative solutions and WARs through volume data analysis and lab experimentation to solve meaningful yield and test problems.

• We lead optimization and continuous improvement efforts on the production screen spec definition processes to minimize waste and meet test time, yield, DPPM requirements.

• Support customer facing and quality teams during partner concerns to understand the issue and fix gaps identified in coverage.

What we need to see:

• BS or MS degree in EE/CE or equivalent experience.

• 5+ years of meaningful industry experience.

• Strong EE fundamentals, knowledgeable in digital design, signal integrity, statistics, timing analysis, fault analysis, sampling and computer architecture.

• Ways to stand out from the crowd:

• Prior board/system level electrical design experience.

• Experience with Perl, C/C++, Windows, and Linux.