NVIDIA

Software Engineer

• Research and develop cutting-edge techniques in deep learning, machine learning, HPC (High Performance Computing), graphs and data analytics, and perform in-depth analysis and optimization to ensure the best performance on NVIDIA current- and next-generation accelerated computing platform, including GPU, CPU and DPU
• Work directly with key customers to understand the current and future problems they are solving and optimize their workloads to maximize performance on our platform
• Collaborate closely with the architecture, research, libraries, tools, and system software teams at NVIDIA to design and develop next-generation architectures, software platforms, and programming models

Technology Engineer – AI

Full-stack Engineer

• Take responsibility for platform software related to GPU systems
• Cover boot flows, driver integration, firmware/BIOS interactions, health monitoring, and system-level capabilities
• Partner with hardware, silicon, driver, and data center/Cloud units
• Launch new GPU platforms, resolve complex system challenges
• Improve performance and power across configurations
• Engage actively in code reviews and contribute to substantial production codebases using solid C/C++ and Python/scripting abilities
• Develop and sustain in-depth knowledge of OS and system software
• Understand how AI workloads map onto NVIDIA architectures

Senior Software Engineer – GPU Platforms

Technical Program Manager

• Collaborate with outstanding engineers and architects to build and deploy large scale GPU computing systems based on NVIDIA's reference supercomputing architectures
• Lead the integration of new AI clusters with datacenter facilities with demanding requirements on power, cooling, and instrumentation
• Coordinate design and fit-out of new datacenter builds, working with both internal engineering teams and external contractors
• Own and produce detailed documentation for the end-to-end process for datacenter fit-out and integration
• Communicate internally with engineering leadership to prioritize and address key issues essential to the success of our largest customers

Datacenter Technical Program Manager

Artificial Intelligence

• Profile and analyze AI workloads on large GPUs and CPUs scale clusters for distributed Deep Learning LLM training and inference focusing at the communication patterns
• Benchmarking, Profiling, and Analyzing the performance to find bottlenecks and identify areas of improvement
• Implement performance analysis tools
• Collaborating with many teams from HW to SW to provide performance analysis insights
• Define performance test planning and set performance expectations

Senior HPC and AI Networking Performance Engineer

• Study and develop cutting-edge techniques in CUDA programming, profiling, optimization
• Work directly with key customers to understand the current and future problems they are solving
• Collaborate closely with diverse groups at NVIDIA to influence design of architectures and software platforms
• Perform in-depth analysis and optimization to ensure best possible performance on GPU architectures

Developer Technology Engineer, AI

Mechanical Engineer

• Analyze architectural requirements and perform trade-off analysis for implementation
• Deliver high performance, area and power efficient RTL Blocks
• Craft micro-architecture specification and implement in high-quality RTL
• Collaborate with chip architects, verification engineers, formal verification engineers, and SoC integration engineers
• Identify potential IP solutions for specific use cases and assist in integration

Senior Digital Design Engineer

• Define, design and develop GPU system software components with focus on power and performance
• Drive end-to-end GPU power management features from idea to productization including chip bring up
• Drive and resolve complex technical issues independently across multiple teams and technical fields
• Influence next generation graphics processing unit composition and system software by building internal architecture specification and develop specification
• Collaborate and communicate effectively with local and remote teams.

Senior System Software Engineer – GPU Power Management

• Drive new products and features through the development process
• Act as a bridge/facilitator between Product Management, Program Management, and Engineering teams
• Map product requirements, PORs (Plan of Record) and roadmaps to documented and actionable engineering programs, projects, and tasks
• Organize engineering execution through sprints and/or target release date management

Senior Technical Program Manager – Omniverse

Engineer

• Drive Timing Analysis and Closure: Lead the timing analysis and closure processes for Nvidia’s GPUs, CPUs, DPUs, and SoCs at block level, cluster level, and full chip level.
• Collaborate with Cross-Functional Teams: Work closely with RTL, DFX, Clocks, and other teams to devise timing closure strategies, create timing constraints, and drive timing and power convergence as well as implement ECOs.
• Contribute to Cutting-Edge Projects: Play a pivotal role in the success of our innovative projects and advancement of our technology. Leverage your expertise to improve timing convergence flows in collaboration with methodology teams.

Senior ASIC Timing Engineer

• Responsible for all aspects of physical design and implementation of GPU and other ASICs targeted at the desktop, laptop, workstation, and mobile markets.
• Participate in establishing physical design methodologies, flow automation, chip floorplan, power/clock distribution, chip assembly and P&R, timing closure.
• Craft designs for static timing analysis, power and noise analysis and back-end verification.

Senior Physical Design Engineer

Solutions Engineer

• Work with NVIDIA Product Teams to understand new product roadmaps and requirements primarily Rack Scale AI Products.
• Finding Optimum Solutions to deploy these products in a Datacenter or a Lab environment using sophisticated design techniques, services and tools.
• Assist in roll-out and deployment of new development features aimed at supporting the latest NVIDIA hardware and technologies.
• Work closely with world-class engineers, architects, technical product managers and application developers setting the best strategies in place for a product launch.
• Defining and implementing full scale solutions for product onboarding into our hosted and private cloud environments.
• Solve sophisticated problems involving multi-site deployments of NVIDIA products and directly contribute to the overall quality of deployments and improve time to market next gen products.
• Collaborate with multi-functional teams, including system engineering, software engineering, mechanical/thermal engineering, operations, data center teams, external vendors, and other partners to successfully deliver a reliable and robust platform from concept to prototype to deployments.
• Integrate and Optimize Cluster Deployment methods and manage SW stack deployments, including provisioning these services into the cloud.

Solutions Architect – Rack Scale AI Systems

• Define, design and develop GPU system software components with focus on power and performance
• Drive end-to-end GPU power management features from idea to productization including chip bring up
• Drive and resolve complex technical issues independently across multiple teams and technical fields
• Influence next generation graphics processing unit composition and system software by building internal architecture specification and develop specification
• Collaborate and communicate effectively with local and remote teams

Senior System Software Engineer – Power and Performance

• Lead the planning and deployment of large scale AI data centers.
• Collaborate with product and engineering teams to understand NVIDIA’s reference architectures for data center infrastructure.
• Support customers and partners in quickly implementing this architecture into advanced and reliable data center designs.
• Review and appraise customers' and partners' infrastructure design plans.
• Deliver guidance, expertise and suggestions to optimize performance, scalability, and cost-effectiveness.
• Assess the operational efficiency, reliability, and readiness of data center infrastructure components before deploying AI/HPC clusters.
• Develop and implement comprehensive audit plans and conduct pre-deployment audits to identify potential issues, risks, and areas for improvement.
• Develop and sustain a strong ecosystem of manufacturers, service providers and partners.
• Implement and make quality assurance processes to ensure that deployments meet established specifications and performance benchmarks.
• Drive continuous improvement initiatives to improve data center infrastructure reliability, resilience, and sustainability.

Solutions Architect – Data Center Buildouts

Infrastructure Engineer

• Craft creative scalable cloud solutions for running millions of jobs, thousands of systems, and petabytes of storage.
• Address exciting challenges in infrastructure such as Kubernetes, job scheduling, multi-region services, resource management, and automated recovery.
• Create agentic workflows for infrastructure.
• Collaborate with customers to understand their needs and develop innovative solutions that cater to their requirements.

Senior Cloud Infrastructure Developer

• Define, design and develop SoC system software components with focus on power and performance.
• Drive end-to-end SoC power management features from idea to productization including chip bring up.
• Drive and resolve complex technical issues independently across multiple teams and technical fields.
• Influence next generation graphics processing unit composition and system software by building internal architecture specification and develop specification.
• Collaborate and communicate effectively with local and remote teams.