High-Tech Jobs

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.

What you'll be doing:

• Onboard new repair partners and manage day-to-day repair operations across our sites, ensuring all facilities achieve turnaround time and quality targets.

• Lead daily operational reviews with repair partners to track key operational metrics, resolve bottlenecks, and enforce accountability for on-time delivery and repair commitments.

• Function as the key intermediary between repair partners and NVIDIA internal teams — Engineering, Quality, Procurement, Logistics, and Planning — to set shared goals and overcome barriers to meeting targets.

• Drive continuous improvement in repair processes, capacity utilization, yield, and quality through structured root-cause and corrective-action initiatives.

• Coordinate repair commit performance (planned vs. actual), monitoring metrics such as on-time completion rate, FA/bonepile recovery time, turnaround time, and test yield.

• Evaluate capital expenditures and repair expenses, and hold quarterly business meetings with repair collaborators.

• Partner with Engineering and Quality to implement repair process controls, engineering change management, and compliance audits.

• Work with Planning and Procurement to ensure supply chain readiness for new service offerings and ongoing repair builds.

• Champion operational excellence by ensuring sites meet quality and delivery commitments, improving metrics.

What we need to see:

• Bachelor’s degree in Engineering, Operations, Supply Chain, or equivalent experience.

• 15+ overall years of hands-on operations experience managing technology repair, refurbishment, or production environments.

• 8+ years ofmanagement/leadershipexperience in reverse logistics or repair operations, including managing multiple sites and vendors (domestic and international).

• Established record of managing daily factory performance, tracking critical metrics, and ensuring vendor accountability.

• Strong understanding of OEM server, PCBA, and system test processes.

• Experience implementing process improvements, capacity planning, and inventory control systems at repair or manufacturing facilities.

• Demonstrated ability to lead cross-functional teams (Engineering, Quality, Planning, Procurement) and deliver measurable performance gains.

• Data-driven decision maker with excellent problem-solving, communication, and vendor management skills.

What You Will Be Doing:

• Bring new products and new technologies to high volume manufacturing

• Deliver datamation solutions for enhanced decision making

• Manage supplier performance evaluation matrix and keep it updated based on changing business needs

• Drive continuous improvement in manufacturing yield, cycle time and product quality/reliability

• Lead change control through qualification and notification

• Lead non-conforming material disposition

• Manage BOM supply chain and optimize sourcing solutions for best capacity and cost

What We Need To See:

• Master’s degree or higher in Engineering or Science with emphasis on Mechanical, Materials Science, Chemical Engineering fields (or equivalent experience)

• 12+ years of validated experience in Flip Chip semiconductor packaging design, process and materials development. Direct experience in advanced assembly technologies such as 2.5D/3D packaging, Photonics packaging experience is desirable

• Solid technical knowledge of materials, process, package design and equipment technologies in substrate, bumping, and chip assembly

• Strong skills in project management and supplier management

• Solid understanding of quality control, statistics process control, gage R&R and DOE techniques

• Good knowledge of packaging industry and its supply chain

• Excellent written and verbal communication skills

• Experience working with multi-functional teams across the world