NVIDIA

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

Systems Engineer

• 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

Full-stack Engineer

• 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

Senior Solutions Architect – Agentic AI

• Assist independent software vendors, ecosystem partners, and lighthouse customers in assessing and adopting technologies within DSX Sim, and Omniverse libraries.
• Architect and demonstrate simulation workflows that help customers build, validate, optimize, and operationalize AI factory digital twins.
• Collaborate with partners to build and validate simulation-ready asset pipelines using OpenUSD, SimReady specifications, engineering data, multi-physics simulation, and operational inputs.
• Drive incorporation of Omniverse libraries (ovRTX, ovPhysx, ovStorage, usd-agents, etc) into partner applications, services, and enterprise workflows.
• Develop reusable reference architectures, demonstrations, sample workflows, benchmarks, and proof-of-concept evaluations that address customer challenges.
• Translate technical and business requirements into clear solution plans while coordinating with sales, product engineering, developer relations, and partner teams to resolve blockers and advance adoption.
• Gather field insights, advocate for partner needs, and contribute technical mentorship that improves product direction, enablement resources, and team execution.

Solutions Architect, Physical AI, Omniverse

• Partner with ISVs on discovery, architecture reviews, technical deep dives, POCs, benchmarks, demos, and production deployment guidance
• Advise on the design, build-out, and optimization of accelerated AI infrastructure, including large-scale clusters
• Support infrastructure design across compute, networking, storage, containers, observability, security, power, and data center operations
• Drive adoption of systems monitoring, telemetry, and management tools to improve cluster utilization, reliability, performance and workload insight
• Build repeatable reference architectures, deployment guides, sizing guidance, benchmark reports, technical playbooks, demos and whitepapers
• Travel up to 20% customer meetings may be required

Senior Solutions Architect – AI Infrastructure, Enterprise ISVs

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

Data Analyst

• Build and deploy scalable ML/AI and optimization models to enhance demand forecasting, optimize capacity allocation, and develop user-specific feature engineering for real-time cloud gaming services.
• Develop reusable framework deployments for data ingestion, processing, and analysis to support dynamic user interventions for targeted business outcomes.
• Acquire and apply domain knowledge of the product and software stack to identify and drive the resolution of data inconsistencies and improve model performance, especially in the context of optimization outcomes.
• Identify, analyze, and interpret trends or patterns in complex data sets using supervised and unsupervised learning techniques, informing prescriptive solutions.
• Design and implement improvements to real-time prescriptive scheduling pipelines, using techniques like linear programming and constraint optimization, to enhance capacity utilization and user retention.
• Improve productivity of the organization by mining petabytes of data for actionable insights for business and engineering, often through prescriptive recommendations.
• Collaborate with a variety of partners to understand requirements, design robust solutions, and guide the team to deliver impactful results.
• Leverage agentic AI to deliver best-in-class automation and programming solutions for complex analytical problems.

Senior Data Scientist, Cloud Gaming – Prescriptive Analytics and Optimization

Architect

• Analyze state of the art DL networks (LLM etc.)
• Identify and prototype performance opportunities to influence SW and Architecture team for NVIDIA's current and next gen inference products
• Develop analytical models for the state of the art deep learning networks and algorithm
• Specify hardware/software configurations and metrics to analyze performance, power, and accuracy
• Collaborate across the company to guide the direction of next-gen deep learning HW/SW

Deep Learning Performance Architect

Hardware Engineer

• Engage in next-generation SmartNIC firmware develop
• Validate the functionalities of firmware and silicon design before tape-out, bring up new silicon when tape-out is done
• Implement new features for congestion control, virtualization, QoS, etc.
• Support local customers to resolve issues in deployment
• Supply creative ideas to improve products and efficiency

Firmware Engineer

• Document and demonstrate advancements in accelerated computing & AI applications through targeted trainings, sharing sessions, whitepapers, blogs, and wiki articles.
• Realize our vision by introducing NVIDIA technology in telecommunication applications for management and operation, and for cloud and edge computing (NFV).
• Develop a keen understanding of customer’s goals and needs, deliver high-value solutions, and support technical trials, proof-of-concepts and customer adoption.
• Lead technical project aspects of complex deployments, including design-in opportunities and responding to RFP/RFI proposals for AI software integration, or edge / cloud / datacenter deployments.