NVIDIA

Director

• Leading a team of dedicated engineers to develop and optimize Workstation GPU system software on Windows and Linux, ensuring our NVIDIA RTX Pro products remain at the forefront of technology.
• Collaborating closely with cross-functional teams, including software engineers, hardware engineers, product managers, and quality assurance, to successfully implement and deliver world-class workstation solutions.
• Defining the technical direction and roadmap for Workstation GPU system software, making strategic decisions to compete effectively in the marketplace.
• Coordinating the development process, from initial concept through to final release, ensuring the highest standards of quality and performance.
• Mentoring and developing team members to foster a collaborative and inclusive work environment where everyone can do their best work.
• Drive market requirements and participate in technical designs with internal and external partners in the Workstation ecosystem.

Director, Workstation Graphics System Software – GPU

Full-stack Engineer

• Create and integrate AI agents to enhance the efficiency, productivity, and quality of VLSI design flows.
• Collaborate on the design and implementation of algorithms and models that can optimize VLSI design processes.
• Contribute to the development of software tools and frameworks that support the integration of AI in VLSI design.
• Analyze and interpret data to identify patterns and insights that can inform the development of AI-driven design methodologies.
• Stay ahead of the latest advancements in machine learning, deep learning, and VLSI build to continuously improve our solutions.

Senior Software Engineer, VLSI AI Agent

• Lead initiatives to transform IT Compute platform architecture to build new service offerings across On-Prem & Cloud.
• Define and implement metrics to measure the efficiency of compute platforms & services and drive efficiency.
• Collect and review system data for capacity and planning purposes, analyze capacity data and develop plans for appropriate level enterprise-wide systems, and coordinate with management personnel in implementing changes.
• Develop and maintain tools for collecting, analyzing, and visualizing data for reporting, alerting, monitoring.
• Collaborate with NVIDIA leadership, senior engineers, program managers, and product managers to develop compelling IT products and services that meet customer needs.

Senior Staff Software Engineer

Business Analyst

• Help analyze business opportunities in priority countries by assessing national and state AI landscapes
• Evaluate government AI strategies and funding
• Identify priority GSIs and ecosystem partners
• Highlight cross-NVIDIA opportunities
• Conduct deep-dive research on assigned countries
• Analyze ecosystem landscapes
• Perform sub-national analysis
• Synthesize findings into clear, executive-ready deliverables
• Present insights and recommendations to the Global Public Sector team

Business Analyst Intern

Software Engineer

• Leading and growing a world-class engineering group dedicated to Data Center Controls, including hiring, mentoring, performance management, and day‑to‑day technical leadership across multiple sites.
• Owning the full life cycle of controls systems (BMS, EPMS, PLC/SCADA) used in electrical, air-based cooling, and fluid-based cooling mechanical systems.
• Tasks include inventing concepts, composing system elements, deployment, operations, and continuous enhancement.
• Partnering with teams in Electrical and Mechanical Engineering passionate about building and construction.
• We define control philosophies, sequences of operation, and reference architectures for new builds, expansions, and retrofits.
• Diving in personally to provide deep technical mentorship on building management systems. This includes electrical power management and vendor platforms such as Cronus and Siemens, or comparable background. This includes configuration, programming, integrations, alarming, and data quality. Diving or comparable experience is considered.
• Driving incident response, root‑cause analysis, standards, and automation that improve uptime, safety, energy efficiency, and operational excellence across NVIDIA’s data centers.

Senior Manager, Data Center Engineering and Controls

Architect

• Design novel GPU and system architectures to advance the forefront of AI Inference performance and efficiency
• Construct, investigate, and test popular deep learning algorithms and applications
• Understand and analyze the relationship between hardware and software architectures as it influences future algorithms and applications
• Build efficient power and performance models of AI inference stack, while capturing minimal but significant information to guide next-gen HW architecture
• Collaborate across the company to guide the direction of AI, working with software, research, and product teams

Senior Deep Learning Performance Architect

• Building joint solutions with ISV and platform partners to enhance the experience for researchers, bioinformatics engineers, and model developers.
• Immersing yourself in CUDA-X libraries and NVIDIA AI, becoming an expert in the SDKs, services, and workflows that constitute it.
• Developing proof-of-concepts and technical reference examples, contributing to community tools with ISV, CSP, and NCP partners.
• Leading technical platform integration roadmaps, while jumping in to solve technical issues as partners integrate with NVIDIA Digital Biology Solutions.
• Working closely with NVIDIA product managers and engineering leads to refine and expand NVIDIA solutions.
• Document what you know and guide others. This can vary from building targeted reference examples for Solutions Architects and other internal collaborators, to as well as for platforms partners — writing whitepapers, blogs, and simply working through hard problems with a customer on a whiteboard.
• Engage with the external community to provide usability feedback to our internal teams to improve product capabilities.

Senior Product Architect – Platforms, Genomics and Life Sciences

Product Marketing

• Work with GTM leaders, individual contributors, and NVIDIA customers to resolve issues and drive action items to resolution.
• Supervise new product introduction deliverables and through ongoing project management.
• Build dashboards to show early indicators of future success and manage meetings to measure progress.
• Complete sales and marketing analysis and reporting on GTM programs and promotions.
• Update databases to scale new worldwide business initiatives.
• Develop playbooks and checklists to supports sales event strategies.

Go-to-Market Strategy Intern

• Contributing to power estimation models and tools for GPU products and systems like NVIDIA DGX.
• Early GPU & System Architecture exploration with focus on energy efficiency and TCO improvements at GPU and Datacenter level.
• Helping with Performance vs Power Analysis for NVIDIA future product lineup.
• Deploying machine learning techniques to develop highly accurate power and performance models of our GPUs, CPUs, Switches, and platforms.
• Understanding the workload characteristics for GenAI/HPC workloads at Datacenter Scale (multi-GPU) to drive new HW/SW features for Perf@Watt improvements.
• Modeling & analysis of cutting-edge technologies like high speed & high-density interconnects.

GPU Power Architect, New College Grad

• Extend and maintain hardware abstraction layers and core system libraries used across the platform.
• Design and implement drivers, runtimes, and data movement/aggregation pipelines supporting workload execution.
• Build and maintain runtime interfaces for launching, monitoring, and managing workloads.
• Improve platform reliability through automation, error reporting, diagnostics, and operational tooling.
• Debug and resolve complex sequencing, initialization, and runtime issues across multi-component systems.
• Partner cross-functionally with hardware engineering, compiler teams, and data center operations to bring features from prototype to production.
• Support new platform bring-up and NPI (New Product Introduction) efforts for new boards and silicon.
• Contribute to engineering excellence through documentation, tooling improvements, code reviews, and knowledge sharing.

Senior Systems Software Engineer

• Collaborate with multi-functional teams to understand customer use cases and compose test strategies
• Carry out functional, integration, regression, and performance testing for software applications
• Identify, debug, and report software defects, inconsistencies, and other quality issues
• Develop and maintain test automation frameworks and scripts using Python and Bash
• Work with planning and tracking systems to manage the release progress and build release indicators
• Participate in code reviews and suggest improvements

System Software Engineer – Networking

Engineer

• Work with some of the best engineers to define verification strategies and complete plans at the full chip level
• Build and continuously reform verification infrastructure and methodologies to meet the demands of next-generation SoCs
• Collaborate with architects, RTL designers, FPGA, and emulation engineers to ensure verification requirements are met for each project

Senior Verification Engineer, SoC

Designer

• Verification for chip blocks/entities according to specifications under challenging constraints and with high orientation to performance
• Daily work involves acquaintance with all aspects of chip development: Design, Micro- Architecture, Firmware, Production, and Verification
• Engage in cutting-edge PCIe generation working on latest PCIe gen7

Senior Chip Design Verification Engineer

Solutions Engineer

• Assist in supporting industry accounts and driving research/influencing/new business in those accounts.
• Assist researchers/engineers on their GPU applications.
• Deliver technical projects, demos and client support tasks as directed by the Solution Architecture leadership team.
• Provide technical support for GPU system deployments.
• Be an industry thought leader on integrating NVIDIA technology into applications built on Deep Learning, High Performance Data Analytics, Robotics, Signal Processing and other key applications.
• Be an internal champion for Data Analytics, Machine Learning, and Cyber among the NVIDIA technical community.

Deep Learning Solution Architect

• Collaborating with front-end, back-end engineers as well as machine learning, deep learning experts.
• Creating human-in-the-loop and management applications.
• Working together with other excellent engineers to build and maintain the next generation services.
• Learn and create valuable features for end users and greatly improve NVIDIA autonomous driving product’s user experience.
• Identify areas to improve service resiliency through industry standard practices.
• Working with NVIDIA global teams to build and maintain the next generation system software for autonomous vehicles fleet including telemetry, cloud services, data processing workflow and much more.
• Explore and implement advanced algorithms to extract valuable insights from big data.
• Utilize modern frontend tech-stack to develop intuitive workflows and user-friendly applications.