NVIDIA

Software Engineer

• Coordinate with the DCEO Operations staff, Collocation provider contacts, the company’s real estate management group, and the environmental health and safety division
• Develop and maintain environmental and sustainability compliance programs, procedures, and training
• Initiate and conduct workshops and training sessions for DCEO operational staff on environmental and sustainability requirements
• Work together with DCEO Operations team, Collocation provider partners, Corporate Real Estate Services, and the Corporate EHS
• Develop a program for regular inspections of facilities to ensure adherence to RCRA, SPCC, ISO, national, local, and environmental and sustainability requirements
• Ensure accurate chemical and waste management
• Coordinate with external firms and internal teams as the primary contact for audits and compliance inspections within DCEO site operations
• Act as Product Manager for assisting with the development of standard and emergency operating procedures
• Leverage AI experience to integrate autonomous solutions into documentation processes.

Data Center Engineering and Operations Environmental Compliance Manager

Machine Learning Engineer

• Provide leadership and strategic mentorship on the management of large-scale HPC systems including the deployment of compute, networking, and storage
• Develop and improve our ecosystem around GPU-accelerated computing including developing scalable automation solutions
• Build and nurture customer and cross-team relationships to consistently support the clusters and address changing user needs
• Support our researchers to run their workloads including performance analysis and optimizations
• Conduct root cause analysis and suggest corrective action
• Proactively find and fix issues before they occur
• Build innovative tooling to accelerate researchers' velocity, troubleshooting, and software performance at scale

Senior AI-HPC Cluster Engineer – MLOps

Full-stack Engineer

• Iterate our software solutions, with a focus on continuing our effort to integrate AI features to deliver capabilities, making it easier for our customers to request, update and find information.
• Securely provide software features, automation and reporting across operational data, purchasing data, power data, lease data.
• Develop and implement software solutions and features, assign engineering tasks to contracted engineers, provide technical guidance and conduct code reviews to ensure operational, quality and security standards are met.
• Maintain documentation for software engineering standards, systems and data pipelines including interfaces to vendors and Nvidia services such as Jira, Nautobot and HANA.
• Define systems standards and documentation
• Develop, validate, and deploy scalable web applications, automation tools, and APIs using innovative technologies and frameworks.
• Define the underlying technology stack, coding standards and development procedures.
• Ensure that engineers are following these standards.
• Experience working in multi-functional teams, partnering closely with systems engineers, product managers, UI/UX designers, QA, and operations to deliver end-to-end solutions.
• Strong understanding of Agile/Scrum methodologies, including sprint planning, backlog grooming, and iterative delivery.
• Evaluate requirements and capture engineering development activities to develop new features.
• Tackle and debug issues across the full stack.
• Drive performance tuning and automation as well as support, maintain and document software functionality and infrastructure.
• Collaborate with the internal teams to fully understand business requirements and provide substantial and measurable results

Senior Full Stack Software Engineer

AI Engineer

• Research and develop techniques to GPU-accelerate high-performance workloads at the intersection of AI and financial markets.
• Work directly with other technical experts in their fields to perform in-depth analysis and optimization of complex AI and HPC workloads.
• Publish and present discovered optimization techniques in developer blogs or relevant conferences.
• Influence the design of next-generation hardware architectures, software, and programming models in collaboration with research, hardware, system software, libraries, and tools teams at NVIDIA.

Senior AI Developer, Technology Engineer – Financial Sector

Program Manager

• Lead technical program management efforts for a given product.
• Drive priorities to ensure products achieve schedule and achievement targets.
• Collaborate closely with a matrixed team of partners from hardware, software, marketing, operations, and other teams.
• Communicate product status to internal teams, including executive teams.
• Apply technical judgment in working with large, cross-functional teams to ensure flawless execution of projects.

Product Program Manager, System LPU

Designer

• Implement, enhance, optimize, and deploy new tools for chip level placement, reshaping and route optimization
• Create innovative algorithms for computational geometry, placement, fast routing etc. to efficiently arrange the blocks in a chip
• Develop and implement new machine learning strategies to improve efficiency of design space exploration
• Improve designer insight, debugging and visualization by extending GUIs built

Senior Software R&D Engineer, VLSI Physical Design

Engineer

• Develop algorithms for AI/DL, data analytics, machine learning, or scientific computing
• Contribute and advance open source Megatron Core and NeMo Framework
• Solve large-scale, end-to-end AI training and inference challenges, spanning the full model lifecycle from initial orchestration, data pre-processing, running of model training and tuning, to model deployment.
• Work at the intersection of compter-architecture, libraries, frameworks, AI applications and the entire software stack.
• Innovate and improve model architectures, distributed training algorithms, and model parallel paradigms.
• Performance tuning and optimizations, model training and finetuning with mixed precision recipes on next-gen NVIDIA GPU architectures.
• Research, prototype, and develop robust and scalable AI tools and pipelines.

Senior Deep Learning Algorithm Engineer, Training Framework

• Develop, refine, and maintain system-level methodologies and software tools for efficient SOC creation, with a primary focus on top-level assembly tools and flows written in C++
• Design, implement, and test robust software components (APIs, libraries, command-line tools) to streamline SOC design and assembly through innovative integration efforts
• Build and improve automated test infrastructure (unit/regression) to ensure correctness, scalability, and long-term maintainability of SOC assembly workflows
• Spot inefficiencies in the SOC/front-end implementation and assembly process and propose actionable improvements (tooling, workflow, usability, performance)
• Collaborate across teams to drive standard methodologies and continuous improvement in SOC development, including requirements gathering, documentation, and user support
• Enable high-quality RTL and integration collateral delivery to downstream teams with thorough quality checks, automation, and reviews
• Occasionally use the top-level assembly tools/flows for IP integration and SOC assembly tasks, helping validate and improve methodology in real projects
• Contribute scripting and infrastructure improvements (e.g., automation, CI, build systems, environment setup) to accelerate methodology adoption

Software Engineer, SOC Design Methodology

• Research and develop techniques to accelerate large scale applications running on NVIDIA’s family of advanced CPU platforms.
• Work directly with other technical experts in their fields (industry and academia) to perform in-depth analysis and optimization of complex database and data analytics workloads to ensure the best possible performance on modern hardware architecture focused on CPU performance.
• Publish and present discovered optimization techniques in developer blogs or relevant conferences to engage and educate the Developer community.
• Influence the design of next-generation hardware architectures, software, and programming models in collaboration with research, hardware, system software, libraries, and tools teams at NVIDIA

Senior Developer Technology Engineer, CPU Performance

Manager

• Establish and maintain effective working relationships with all collaborators
• Understand the high and low-level technical architecture and be able to facilitate debate and drive decisions on appropriate solutions
• Ensure that company requirements are produced to standard promptly.
• Develop & present comprehensive technical solutions to customers
• Communicate and hold conference calls with internal teams, customers, and partners
• Lead complex installations
• Report and advance all observed problems to proper operational partner concern points
• Handle the communication of project changes and release notices to customers
• Document technical and operational procedures clearly and concisely
• Be willing to work irregular hours as required

Senior Project Delivery Manager – NVIS

• Implement language and multimodal model inference as part of NVIDIA Inference Microservices (NIMs).
• Contribute new features, fix bugs and deliver production code to TRT-LLM, NVIDIA’s open-source inference serving library.
• Profile and analyze bottlenecks across the full inference stack to push the boundaries of inference performance.
• Benchmark state-of-the-art offerings in various DL models inference and perform competitive analysis for NVIDIA SW/HW stack.
• Collaborate heavily with other SW/HW co-design teams to enable the creation of the next generation of AI-powered services.

Senior DL Algorithms Engineer – Inference Performance

Artificial Intelligence

• Formulate benchmarking methods for high-performance computing and AI tasks.
• Perform and bring these methods to completion on large-scale GPU clusters.
• Assess performance metrics to detect optimization opportunities and upgrade architecture.
• Develop and maintain telemetry infrastructure to capture performance data.
• Collaborate closely with hardware engineering, software development, and customer-facing teams to define performance requirements, fix bottlenecks, and validate configurations against real-world workloads.
• Deploy and manage observability stacks including monitoring tools like Prometheus, visualization platforms such as Grafana, NVIDIA's DCGM, and custom telemetry solutions to provide actionable insights into cluster health, utilization, and performance trends.
• Work directly with engineering and collaborate with internal partners to understand their performance requirements, conduct on-site benchmarking engagements, and deliver detailed analysis and recommendations for workload optimization.
• Maintain extensive knowledge of industry-standard benchmarks in advanced computing and machine learning fields such as HPL, HPCG, MLPerf, and NCCL tests.
• Contribute to developing new benchmarking methodologies for emerging workloads.

AI Benchmarking and Telemetry Engineer

• Define the best engineering optimization practice from component to system levels as part of the product development cycle.
• Perform structural and dynamic analysis
• Perform Multiphysics analysis across various physical domains to reflect real use case conditions and feedback to design improvement
• Produce and maintain models generated from in-house and commercially available software codes that simulate mechanical loading conditions, dynamic environments (Shock&Vibration), and thermos-mechanical simulations
• Familiar with customized coding for commercially available tool to further expand the tool capability
• Document analysis through formal reports that are clear, detailed, and timely
• Present analysis reports and test results at program reviews
• Provide rapid analysis results to support conceptual studies and rapid prototype development
• Assess and propose new simulation strategies to improve product development
• Mentor junior engineers and cross-train other engineering fields

Senior Design Optimization Engineer – LPU Packaging

• Primary responsibilities will include deploying, managing, and maintaining AI infrastructure for new and existing customers.
• Be the domain expert with customers during planning calls through implementation.
• Handover-related documentation and perform knowledge transfers required to support customers as they begin rolling out some of the most sophisticated systems in the world!
• Provide feedback to internal teams such as opening bugs, documenting workarounds, and suggesting improvements.

AI Compute Engineer

• Perform advanced Static Timing Analysis (STA) at chiplet and FC level.
• Running Prime Time, review and debug timing paths, understand constraints, sdc generation, timing ecos generation.
• Identify convergence risks and work closely with physical design, RTL and DFT teams, ensuring convergence throughout various project stages.
• Responsible for a full timing closer and quality approval from pre-layout STA model through signoff.