NVIDIA

Full-stack Engineer

• Be responsible for the integration of SW components to switch operating system
• Define, develop and design a process for integration and customer issues
• Lead customer success activities, including feature development and customer engagement.
• Work with a continuous integration system, regression tools
• Be responsible for NVIDIA NVL, IB
• Innovate! Bring NVIDIA's networking products to shine in customer's view

Director, Software Engineering – NVlink Switch

Artificial Intelligence

• Develop datasets and moderator models for evaluating LLM models and end-to-end systems for Content Safety, ML Fairness
• Research and implement cutting-edge techniques for bias detection and mitigation in LLMs and systems
• Define and track key metrics for responsible LLM behavior and usage
• Collaborate with other engineers, data scientists, and researchers to develop and implement solutions to content safety and ML fairness challenges

AI Safety Scientist, Deep Learning

• Work closely with passionate engineers to design, develop, optimize, debug, unit test, document and maintain next-generation graphics and computing features for NVIDIA GPUs
• Collaborate with many internal teams (software, hardware, architecture, QA and OEM support), partners and customers to define new products and features, and resolve issues.

Senior System Software Engineer – GPU Virtualization

• Develop efficient infrastructure and tools for automating complex software processes
• Implement advanced test harnesses, benchmarking frameworks, and analytical tools to characterize and optimize the performance and efficiency of our software and hardware platforms
• Work with engineering teams to understand needs, define requirements, and deliver efficient solutions
• Set performance goals, monitor feedback, analyze data, and make continuous improvements for system reliability
• Contribute to defining technical strategies and roadmaps for our platform automation initiatives

Senior System Software Engineer, AI Data Platform

Designer

• Ensuring robust power integrity in physical design to optimize power delivery
• Design and optimize physical design solutions for power integrity
• Perform power integrity analysis and mitigation
• Collaborate with hardware and design teams on power delivery strategies
• Utilize tools and flow in advance technology to meet project development

Physical Design Engineer, Power Integrity

Sales

• Lead the AI Edge and Embedded business strategy for EMEA, identifying and accomplishing high-impact opportunities that drive market expansion and customer success.
• Strengthen and scale our partner network by encouraging collaboration across distributors, NPN partners, and direct OEM engagements to amplify NVIDIA’s reach and influence.
• Bring global initiatives to life across the region, tailoring product launches and marketing campaigns that resonate with customers and partners in EMEA.
• Grow and develop a world-class team, identifying opportunities for growth and attracting top-tier talent to support ambitious business goals.
• Build a culture of innovation, collaboration, and accountability — mentoring team members to excel and celebrating shared success.
• Be the voice of EMEA across NVIDIA’s global business units, ensuring regional strategies align seamlessly with global priorities and vertical market objectives.
• Lead with data-driven rigor to manage a robust business pipeline, ensuring predictable, scalable revenue growth.
• Track progress, share key metrics, and showcase major success stories that demonstrate how our technologies are redefining industries.

Senior Manager, Embedded Sales

Engineer

• Collaborate with Technical Package Lead and different design teams
• Implement high speed/density ASIC packages
• Perform substrate breakout patterns for ASIC packages
• Optimize package pinout incorporating system level trade-offs of pins assignment
• Help perform package routing, placement, stack-up, reference plane and power distribution using Cadence APD or SiP tool suite
• Propose layout design trade-offs to the Technical Package Lead for resolution and implementation
• Conduct design feasibility studies to evaluate the Package design goals for size, cost, and system performance
• Develop symbols and CAD library databases using Cadence APD design tools
• Develop methodologies to improve layout productivity

Senior Package Layout Engineer – Hardware

• Set the Strategy: Define the multi‑year technical strategy and roadmap
• Manage the Portfolio: Develop the operating model for NIM Factory
• Lead Leaders: Guide the NIM Factory engineering organization
• Accelerate Day-0 Model Delivery: Manage the factory systems and platform capabilities
• Establish the Operational Standard: Define and guide the full platform standards
• Own Reliability, Security, and Compliance Outcomes: Partner with SRE and security leadership
• Champion Open Source and Standards: Lead our upstream strategy and partnerships

Director, Software Engineering – NIM Factory

DevOps Engineer

• Develop and maintain CI/CD pipelines to automate the build, test, and deployment processes, and improve performance by addressing bottlenecks.
• Managing tools and enabling automations for redundant manual workflows via Gitlab, Jenkins, Terraform, etc
• Improve monitoring and observability mechanisms in all aspects of content services
• Optimise infrastructure for performance, reliability, and cost efficiency
• Collaborate with software engineering teams to streamline deployment processes and reduce operational overhead
• Participate in the on-call rotation and identify and resolve content-related service issues to ensure our systems operate flawlessly.

Senior DevOps Engineer

Developer Relations

• Serve as a trusted technical advisor to Inception AI-native startups, understanding their critical workloads and guiding technical enablement across the NVIDIA stack
• Partner with startups to integrate NVIDIA foundational models, SDKs, and frameworks, enabling co-innovation and the development of next-generation AI solutions
• Map, build, and expand a rich ecosystem of strategic startups to champion NVIDIA technologies, track ecosystem trends, and multiply growth opportunities
• Collaborate multi-functionally with solution architects, engineering, product management, and marketing to drive startup engagement and optimize partner adoption strategies
• Work closely with startup engineering teams, technical leaders, and decision-makers to unpack goals, tackle technical challenges, and endorse protocols for successful integrations
• Advocate for the startup's technical needs and funnel feedback to NVIDIA’s internal product and engineering teams, supplying actionable insights from field deployments to influence product roadmaps

Developer Relations Manager – Inception Program Startups

• Design, implement, and operate cloud platform services that provide GPU‑accelerated IaaS on top of Kubernetes and KubeVirt.
• Develop and extend Kubernetes and KubeVirt components (e.g., operators/controllers, CRDs, device plugins) to support GeForce NOW and new NVIDIA hardware platforms.
• Drive the underlying technology stack: influence architecture, coding standards, observability, and deployment methodology for high‑scale, high‑availability services.
• Collaborate closely with product, hardware, and other engineering teams to deliver new capabilities end‑to‑end, including leading design discussions and aligning engineering leads on architecture and technology choices.
• Lead performance tuning, scalability improvements, and pervasive automation across the stack (provisioning, testing, deployment, operations).
• Own and document system and software architecture, designs, and implementation details for the services you build.
• Mentor engineers on the team and help foster a culture of engineering excellence, learning, and collaboration.

Senior System Software Engineer, Kubernetes, KubeVirt

Machine Learning Engineer

• Work with some of the brightest minds in a leading AI company to develop a leading machine learning framework, NVIDIA PhysicsNeMo, for our academic and industrial partners to construct digital twins and machine learning simulation surrogates for real world science and engineering problems
• Work with internal project teams to validate applications built using the framework on Nvidia’s products
• Characterize and optimize scientific AI workloads on the latest NVIDIA platforms
• Stay up to date with the latest research and innovations in deep learning techniques, implement and experiment with new ideas to develop and enhance NVIDIA's deep learning technologies with focus on simulations

Senior Machine Learning Performance Engineer – Physics

Platform Engineer

• Spearhead automation engineering initiatives to streamline and optimize deployment workflows.
• Manage, configure, deploy, and provision Kubernetes clusters at scale.
• Lead the design and implementation of CI/CD pipelines, ensuring a robust, automated, and efficient delivery process.
• Develop and implement security tooling to safeguard our cloud infrastructure and applications against threats.
• Architect solutions to improve the developer experience and streamline application delivery through GitOps.
• Develop Infrastructure as Code (IaC) modules and scripts to automate the provisioning and management of cloud resources.
• Decouple applications from infrastructure and abstract configuration to simplify microservice development.
• Engage with cross-functional teams to ensure seamless integration across all major cloud service providers.

Senior Platform Engineer

• Work with some of the brightest minds in a premier AI company to develop leading machine learning frameworks, NVIDIA PhysicsNeMo and NVIDIA Earth2Studio, for our academic and industrial partners to build scientific ML technology and workflows for weather, climate, and earth system modeling.
• Work with internal project teams to validate applications built using the framework on NVIDIA’s products, and integrate new functionalities from internal or external projects into the platform
• Stay up to date with the latest research and innovations in deep learning techniques, implement and experiment with new ideas to develop and enhance NVIDIA's Earth-2 technologies, with a focus on weather & climate AI

Senior Scientific Machine Learning Engineer

• Architect, build, plan, implement, and operate complex PaaS for GPU cloud services.
• Drive the underlying technology stack and implementation methodology.
• Work closely with collaborators, customers, UX/UI designers, and front-end engineers on developing new products or enhancing existing features.
• Ensure consistency across modules and/or products within the team.
• Champion the adoption of development practices that prioritize testing, including advancing test automation and CI/CD.
• Maintain a customer-centric approach by supporting, maintaining, and detailing software functionality.