NVIDIA

Business Development Rep

• Serve as the trusted strategic advisor, problem solver, and champion for customers and partners in the Automotive industry and ecosystem.
• Engage with customer and partner business teams, technical leaders, and decision-makers to identify goals, tackle business challenges, and guide them in their AI journeys.
• Foster innovation speed and positive business impact by highlighting the value of groundbreaking technologies in solving real world problems in the Automotive industry.
• Accelerate critical business opportunities.
• Map, track, and monitor the partner ecosystem to identify growth opportunities.
• Collaborate multi-functionally with solution architects, engineering, product management, and marketing to drive engagement.
• Supply actionable insights from field engagements to influence product roadmaps.

Business Development Lead, Automotive

Full-stack Engineer

• Work with a geographically distributed partner organisation to understand, modify and improve CPU Compiler SW at NVIDIA.
• Analyse AI workloads to champion improvements in both new hardware and compiler toolchain and improve hardware-software co-design.
• Contribute new features and optimisation techniques targeting NVIDIA CPUs engaging with upstream and open source communities.
• Develop compiler SW that is optimised for performance.
• Be part of a team that is at the centre of artificial intelligence, high-performance computing and data centre technologies.
• Contribute towards the development of next generation compute

Senior CPU Compiler Performance Engineer

Infrastructure Engineer

• Design, build, and operate the Kubernetes platform that powers GNI network automation, telemetry, and operations across data center, colocation, and cloud environments.
• Own the lifecycle management for GNI Kubernetes environments, including cluster onboarding, upgrades, capacity, availability, and recovery.
• Develop production-quality software and automation for cluster provisioning, validation, upgrades, remediation, and safe multi-cluster delivery through GitOps.
• Provide production support for network services hosted on the platform, working with Network Automation and service teams that retain ownership of application architecture, code, and features.
• Diagnose complex Kubernetes platform and hosted-service failures involving control-plane health, cluster networking, storage, scheduling, workload placement, and multi-cluster dependencies.
• Drive issues from initial signal through verified resolution.
• Define production-readiness and observability standards for the platform and hosted network services, including health signals, capacity, alerts, runbooks, and recovery.
• Participate in CFR’s production on-call rotation, including scheduled after-hours and weekend coverage.
• Lead incident response and recovery, then drive corrective actions to completion.

Senior Platform Engineer, Network Infrastructure

• Work across the full stack of a distributed systems platform, from crafting gRPC contracts to building secure sandbox runtimes.
• Implement and harden network security features, including policy enforcement, L4/L7 proxies, and secure inter-service communication using mTLS.
• Develop core platform components such as inference routing, ensuring model provider adapters, credential management, and protocol translation integrate seamlessly with the sandbox and gateway.
• Build reliable configuration and control plane systems that handle state divergence, implement reconciliation loops, and support safe merging and hot-reloading policies.
• Own the operability experience by creating effective CLI tools, managing release automation, and instrumenting all systems for observability with structured logging and distributed tracing.

Software Engineer, OpenShell

• Apply knowledge of compute programming models and compute architecture to build tools that provide actionable feedback to compute developers
• Work in existing driver code and application code as well as writing new shared libraries and targeted performance tests
• Develop the Compute Sanitizer (which is a suite of memory checker) tools for GPUs running on Linux, Windows, and embedded operating systems
• Work with tools, compiler, architecture and driver teams to design, implement and verify new features in the Compute Sanitizer stack
• Collaborate with internal and external partners including other peer organizations within NVIDIA
• Effectively estimate and prioritize tasks in order to create a realistic delivery schedule
• Write fast, effective, maintainable, reliable and well-documented code
• Provide peer reviews to other engineers, including feedback on performance, scalability and correctness
• Document requirements and designs, and review documents with teams throughout NVIDIA
• Mentor junior engineers

Senior Software Engineer, Compute Sanitizer – GPU

AI Engineer

• Design, develop, and improve scalable infrastructure to support the next generation of AI applications
• Drive improvements in architecture, performance, and reliability
• Collaborate across hardware, software, and research teams
• Stay informed of the latest advancements in AI infrastructure

Senior Applied AI Engineer

Systems Engineer

• Work on end‑to‑end performance and scalability analysis across the Kubernetes‑based accelerated runtime stack (control and data planes), including NVIDIA components such as GPU Operator, Network Operator, node-feature-discovery, topograph, dra-driver-nvidia-gpu, and nvsentinel, tracking issues from orchestration down to the metal.
• Design and contribute upstream architectural changes to the Kubernetes control plane and related projects to enable reliable operation at hyperscale cluster sizes, doing in the open what today’s hyperscalers typically do privately.
• Improve container startup and cold‑start latency to enable smooth, low‑latency inference scaling on Kubernetes across thousands of GPU nodes, ensuring the AI runtime stack scales without creating API server pressure or operational fragility.
• Assess, improve, and contribute to open‑source projects that make Kubernetes an outstanding platform for AI workloads (for example, Grove and gateway-api‑inference‑extension), composing their architectures with scalability, resilience, and multi‑node training/inference in mind.
• Advance scalability and performance of confidential containers (CoCo) on Kubernetes so encrypted inference workloads meet stringent efficiency and latency requirements in production.
• Use DSX and related large‑scale simulation infrastructure to model full AI‑factory deployments and validate scalability across thousands of simulated GPUs, catching failures that emerge only at scale before hardware arrives.
• Collaborate with AI researchers, developers, customers, and upstream communities to design automated, at‑scale workload tests (including replay of production agent traces), build monitoring/analysis tooling, and integrate continuous performance and scale testing into modern CI/CD workflows.
• Document methods and results clearly and present findings internally and at industry events (for example, KubeCon, GTC), while actively engaging with upstream groups (Kubernetes SIG Scalability, CNCF, and NVIDIA OSS communities) to influence and validate AI workload performance and scalability directions.

Systems Software Engineer – Accelerated Kubernetes Performance and Scale

Production Engineer

• Design, implement, and support large-scale storage clusters, ensuring scalability, high availability, and data integrity.
• Develop and maintain storage monitoring, logging, and alerting systems to ensure proactive detection and resolution of performance issues.
• Work with AI/ML workloads to improve storage architectures for low-latency access, efficient caching, and high-throughput performance.
• Improve the lifecycle of storage services – from inception and design to deployment, operation, and continuous optimization.
• Support storage services before they become available through activities such as system build consulting, developing automation frameworks, capacity management, and launch reviews.
• Maintain production storage infrastructure by supervising availability, latency, and system health, leveraging predictive analytics and AI-driven automation.
• Optimize storage efficiency through compression, deduplication, tiering strategies, and intelligent workload placement.
• Scale storage systems sustainably using AI/ML-driven automation, policy-based tiering, and dynamic data migration techniques.
• Ensure data security and compliance by implementing encryption, access controls, and auditing mechanisms for storage systems.
• Practice sustainable incident response and blameless root cause analysis.
• Be part of an on-call rotation to support storage and production systems.

Senior Storage Production Engineer – DGX Cloud

DevOps Engineer

• Manage end-to-end provisioning of network services (wavelengths, Ethernet, IP transit, dark fiber & subsea IRU).
• Partner with carriers and data centers to track orders, delivery, and handoff.
• Document LOAs, CFAs, and circuit details in inventory and ticketing systems.
• Support circuit testing/troubleshooting during turn-up.
• Source and procure POP space, power, cross-connects and related services.
• Lead vendor selection, contract negotiations, and SLA management.
• Coordinate PoP handover schedules with the network deployment and engineering teams, legal and procurement.
• Manage site readiness schedules, equipment logistics and service requests.
• Plan for power capacity, rack utilization and future growth potential.
• Monitor vendor performance, operational costs and contract compliance.
• Maintain documentation for contracts, power allocations and deployment standards.
• Support PoP expansions, upgrades and decommissioning activities.
• Keep projects on track in a fast-moving, deadline-driven environment.

Senior Network Deployment Engineer, PoP Management

• Develop Java, Scala and CUDA/C++ libraries to accelerate DataFrames and I/O operations on common file formats such as Parquet, ORC and JSON
• Enable interoperability with table formats such as Apache Iceberg and Delta Lake, and metastores such as Unity Catalog
• Work with open source communities to enhance libraries like NVIDIA cuDF, CCCL and UCX through technical discussion and code contributions
• Collaborate with distributed systems teams to craft solutions to distributed processing problems challenges at large scale
• Provide recommendations and feedback to teams regarding decisions surrounding topics such as infrastructure, continuous integration and testing strategy
• Build, test and optimize CUDA/C++ libraries across different platforms

Principal Systems Software Engineer

Account Manager

• Attain a minimum of 100% Quota attainment selling Enterprise product and solutions to Enterprise Accounts
• Identify and build key accounts into strategic partners, and drive sustaining revenue, market share growth, and product footprint
• Understand and deliver NVIDIA value proposition, key features, product messages, positioning
• Be responsible for all aspects of strategy creation and implementation, forecasting, sales account management, training, and education to your customers.
• Establish relationships with key executives to achieve endorsement of NVIDIA solutions and adoption of same by their developer teams
• Work closely with partners, OEMs, ODMs and the ISV ecosystem to build and implement go-to-market plans for accelerated growth and adoption of the enterprise solution family.
• Contribute to the long-term success of our team by being a collaborative leader amongst your peers.
• Consistently striving to improve and reinvent yourself.
• Engage appropriate NVIDIA resources as part of a virtual sales team

Account Manager, Healthcare MedTech

• Dig deep into new and important CUDA features, evaluate them and experiment with them to provide developer-centric insights to help inform product development.
• Craft compelling technical content, such as tutorials, guides, and blog posts to help enhance developer effectiveness using CUDA.
• Deliver technical workshops, webinars, and presentations to educate and empower developers to build innovative solutions using NVIDIA’s CUDA Platform.
• Capture market insights and developer feedback to advise product roadmap decisions and find opportunities for innovation and differentiation.
• Work effectively across NVIDIA with groups such as Product Management, Product Marketing, Engineering and Technical Sales to achieve business goals.

Senior CUDA Technical Marketing Engineer

Cloud Engineer

• help drive the efficiency, reliability, and scalability of the systems that power our global business operations
• define how we implement innovative automation and support solutions
• join the core group at NVIDIA working to architect and build scalable and distributed NGC Cloud services
• be a technical leader on various projects across the platform
• drive operational excellence for secure, scalable secrets management, artifact management

Principal Software Engineer – Cloud Services

Software Engineer

• Collaborate with developers, researchers, and framework maintainers across industries to identify and resolve performance challenges in diverse workloads such as AI, data analytics, simulation, and numerical computing.
• Profile, analyze, and optimize CPU performance from application-level algorithms down to low-level microarchitecture.
• Contribute to open-source frameworks, key software stacks, reference implementations, and performance libraries to unlock full CPU potential.
• Work closely with NVIDIA’s architecture, research, libraries, tools, and system software teams to improve our overall platform performance.
• Provide insights that shape next-generation CPU designs, compiler toolchains, and development workflows for better developer productivity and throughput.

CPU Performance Developer, Technology Engineer

Solutions Engineer

• Lead technical delivery for strategic Agentic AI partner engagements
• Design and build enterprise-grade agentic systems
• Lead deep architecture reviews with partner engineering teams
• Build hands-on PoCs, benchmarks, reference architectures
• Guide partners on model customization and post-training workflows