NVIDIA

Solutions Engineer

• Work with Cloud Service Providers to develop and demonstrate solutions based on NVIDIA’s ML/DL and data science software and hardware technologies
• Build and deploy AI/ML solutions at scale using NVIDIA's AI software on cloud-based GPU platforms
• Build custom proofs of concept addressing customers’ critical business needs with NVIDIA hardware and software
• Partner with Sales Account Managers or Developer Relations Managers to identify and secure new business opportunities for NVIDIA products and solutions
• Prepare and deliver technical content to customers, including presentations and workshops
• Conduct regular technical customer meetings covering project and product roadmaps, feature discussions, and new technologies
• Establish close technical ties with customers to facilitate rapid resolution of customer issues
• Engage directly with developers, researchers, and data scientists at strategic technology customers
• Work with business and engineering teams on product strategy
• Drive end-to-end technology solutions based on customer business needs

Solutions Architect, AI and ML

• Engage with customers, partners, and NVIDIA software engineers to support applications and platforms leveraging NVIDIA technology.
• Partner with industry and account teams to understand customer goals, strategies, and technical needs.
• Define and deliver high-value technical solutions.
• Document knowledge and teach others through targeted samples, whitepapers, blogs, wiki articles, and customer whiteboarding.
• Integrate NVIDIA technology into Manufacturing use cases involving AI, HPC, enterprise GPU, and networking architectures across datacenter and edge applications.
• Strategically partner with lighthouse customers and industry-specific solution partners targeting NVIDIA’s computing platform.
• Support customers and partners in technical engagements.

Senior Solutions Architect, Industrial Robotics

• Support Business Development and Sales teams as part of a Solutions Architecture team, partnering with Industry Business leads, Account Managers, and Developer Relations managers across Industrial Engineering accounts.
• Work directly with engineering-software developers and customer simulation teams in a customer-facing setting.
• Help developers GPU-accelerate and scale CAE/CFD/FEA solvers and structural, thermal, and fluid-dynamics workloads on NVIDIA accelerated computing and HPC platforms.
• Apply physics-informed ML and surrogate modeling, including NVIDIA PhysicsNeMo / Modulus, and NVIDIA Omniverse digital twins to compress design, simulation, and optimization cycles.
• Analyze simulation and engineering application architectures and identify opportunities for acceleration.
• Provide feedback and collaborate with engineering, product, and research teams.
• Deliver trainings, hackathons, and technical demonstrations on NVIDIA solutions and platforms.

Senior AI Solutions Architect – Industrial Engineering

• Recruit and manage a team of solutions architects, system/network engineers, and software engineers focused on large-scale GPU and AI networking deployments.
• Set priorities, allocate resources, mentor team members, and ensure high-quality customer delivery across concurrent projects.
• Participate directly in technical reviews, design decisions, and critical debugging efforts.
• Provide subject-matter expertise in GPU and network systems and serve as senior technical contact for strategic customers and emerging AI labs.
• Lead compute and network configuration and performance debugging to deliver reliable clusters.
• Guide compute, network, and software architecture discussions and support server, network, and cluster bring-up, including on-site data center work where needed.
• Collect and synthesize customer-specific requirements.
• Partner with GPU and Network Systems Engineering, Product Management, and Sales to influence roadmaps and reference designs.
• Expand NVIDIA solution engagements across strategic AI-lab customers.

Manager, Solutions Architecture – Emerging AI Labs

• Recruit and manage a team of solutions architects, systems/network engineers, and software engineers focused on large-scale GPU and AI networking deployments.
• Set priorities, allocate resources, mentor team members, and ensure high-quality customer delivery across concurrent projects.
• Participate directly in technical reviews, design decisions, and critical debugging efforts.
• Provide subject-matter expertise in advanced GPU and network systems as senior technical contact for a strategic AI lab.
• Lead compute and network configuration and performance debugging for reliable clusters.
• Guide compute, network, and software architecture discussions and support server, network, and cluster bring-up, including on-site data center work where needed.
• Collect and synthesize customer-specific requirements.
• Partner with GPU and Network Systems Engineering, Product Management, and Sales to influence roadmap priorities and package reference designs and solutions.
• Partner with customer engineering and security stakeholders to understand security requirements and translate them into scalable AI infrastructure.
• Lead customer meetings, communicate status and risks, and produce design documents, debug summaries, and presentations.

Manager, Solutions Architecture – AI Labs

• Define reference architectures and blueprints for end-to-end solutions integrating GPU and networking into data-center solutions
• Support account teams in identifying business opportunities for NVIDIA Networking products and technology solutions
• Work with Sales teams and Product Marketing to develop customer solutions
• Provide technical account management for NVIDIA Networking product key accounts
• Conduct customer meetings for product updates and introduce new technology solutions
• Deliver product roadmap presentations to customers and technology partners
• Respond to RFP/RFI proposals covering network designs for AI factories, HPC clusters, cloud, and enterprise environments
• Build and deliver custom-tailored product demonstrations and proofs of concept
• Manage complex networking deployments and design-in opportunities
• Analyze and troubleshoot technology performance issues at customer sites
• Prepare and deliver technical training presentations
• Provide constructive engineering feedback on product requirements and evolution, including enhancement requests supported by business evidence

Senior Network Solution Architect

• Define reference architectures and blueprints for end-to-end solutions integrating GPU and networking into data-center solutions
• Support account teams in identifying new business opportunities for NVIDIA Networking products and technology solutions
• Work closely with Sales teams and Product Marketing to deliver customer solutions
• Provide technical account management for NVIDIA Networking product key accounts
• Conduct customer meetings for product updates, technology introductions, and roadmap presentations
• Respond to RFP/RFI proposals covering network designs for AI factories, HPC clusters, cloud, and enterprise environments
• Build and deliver custom-tailored product demonstrations and proofs of concept
• Manage complex networking deployments and design-in opportunities technically
• Analyze and troubleshoot performance issues with new technology at customer sites
• Prepare and deliver technical training presentations
• Provide constructive feedback to engineering on product requirements and evolution, including requests for enhancements supported by business evidence

Compliance

• Develop and coordinate a comprehensive global risk and compliance framework aligned with NVIDIA’s strategic objectives
• Guide and direct a team of compliance professionals to maintain adherence to applicable regulations and standards
• Collaborate with cross-functional teams to identify and mitigate risks across business units
• Build and implement risk assessment programs and continuously improve risk management processes
• Advise senior leadership on risk and compliance topics and risk mitigation strategies
• Execute compliance programs, including policy development, training, and audits
• Drive continuous improvement initiatives to improve risk and compliance efficiency

Senior Director, Global Risk and Compliance

Hardware Engineer

• Work closely with the architecture and different software design teams
• Implement new features in the core of NVIDIA NIC firmware in pre and post silicon environment
• Develop verification tests for advanced features in a highly complex and sophisticated Firmware testing environment
• Gain a deep understanding of system debug, networking technology and stacks, as well as the HW/FW/SW relationship
• Learn how a big software project is operated, maintained, qualified and released, and how Hardware and Firmware are developed

Firmware Engineer

Full-stack Engineer

• Craft and develop robust inference software scalable across multiple platforms for functionality and performance
• Analyze and optimize Large Language Model (LLM) inference performance
• Follow academic and industrial developments in artificial intelligence and feature-update TensorRT-LLM
• Implement kernels and runtime features supporting new LLM models and inference algorithms
• Provide feedback on architecture and hardware design and development
• Collaborate across software, research, and product teams to guide deep learning inference direction

AI Computing Software Development Engineer, TensorRT-LLM

• Optimize system software for NVIDIA automotive performance platforms with Safe RTOS
• Collaborate with Hardware Architecture, DriveOS, Power, and Test teams to track boot and runtime performance benchmarks
• Supervise micro benchmarks and industry-standard benchmarks across IPs
• Develop innovative features in automotive profiling tools with AI assistance
• Benchmark the hypervisor and minimize overhead on ARM systems
• Collaborate with the ADAS/AV team to optimize the next-generation NVIDIA stack on Tegra platforms

Senior System Software Engineer, Automotive Performance

Engineering Manager

• Lead, mentor, and scale a high-performing engineering team focused on deep learning inference and GPU-accelerated software
• Drive the strategy, roadmap, and execution of NVIDIA’s inference frameworks engineering, focusing on Client AI
• Partner with internal compiler, libraries, and research teams to deliver optimized inference pipelines across NVIDIA accelerators
• Oversee performance tuning, profiling, and optimization of large-scale models for LLM, multimodal, and generative AI applications
• Guide engineers in adopting CUDA, Triton, CUTLASS, and multi-GPU communication technologies
• Represent the team in roadmap and planning discussions
• Foster technical excellence, collaboration, and continuous innovation

Engineering Manager, Deep Learning Inference

Systems Engineer

• Advance the state of the art in foundation model development, training, and deployment
• Design scalable systems for preparing high-quality multimodal datasets for frontier foundation model training
• Develop algorithms and systems that improve the scalability, efficiency, and cost of large-scale pre-training and post-training
• Advance techniques that improve inference performance, reduce deployment cost, and enable efficient serving across cloud and edge platforms
• Develop reusable infrastructure and contribute new model support to NVIDIA's open-source GenAI training platform
• Collaborate with research, product, and infrastructure teams to design new algorithms and optimize existing systems
• Contribute to NVIDIA's open-source AI stack, including Megatron-LM, Megatron Bridge, and NeMo-RL

Senior AI Systems and Algorithms Engineer

• Explore, research, and prototype systems optimizations for advanced deep learning models at the intersection of high-level deep learning frameworks and low-level CUDA.
• Architect and optimize distributed computing systems from single-node to cluster-scale supercomputing environments.
• Design, implement, and optimize custom high-performance CUDA kernels for emerging neural network architectures and workloads.
• Analyze hardware-software interactions to identify and resolve performance bottlenecks in training and inference pipelines.
• Collaborate with AI researchers, hardware and software architects, kernel and compiler authors, and CUDA driver experts to co-design systems and algorithms.
• Develop exploratory tools and runtime systems to profile and accelerate new deep learning paradigms.
• Write clean, effective, and maintainable code and transition prototypes into open-source releases, framework integrations, internal tools, or commercial products.

Software Engineer, CUDA Deep Learning Systems

• Explore, research, and prototype systems optimizations for advanced deep learning models at the intersection of high-level deep learning frameworks and low-level CUDA through modeling, simulation, and silicon prototyping
• Architect and optimize distributed computing systems from single-node to cluster-scale supercomputing environments
• Design, implement, and optimize custom high-performance CUDA kernels for emerging neural network architectures and workloads
• Analyze hardware-software interactions to identify and resolve performance bottlenecks in training and inference pipelines
• Collaborate with AI researchers, hardware and software architects, kernel and compiler authors, and CUDA driver experts to co-design systems and algorithms
• Develop exploratory tools and runtime systems to profile and accelerate new deep learning paradigms
• Write clean, effective, and maintainable code and transition prototypes into open-source releases, framework integrations, internal tools, or commercial products

Solutions Architect, AI and ML

Senior Solutions Architect, Industrial Robotics

Senior AI Solutions Architect – Industrial Engineering

Manager, Solutions Architecture – Emerging AI Labs

Manager, Solutions Architecture – AI Labs

Senior Network Solution Architect

Senior Network Solution Architect

Senior Director, Global Risk and Compliance

Firmware Engineer

AI Computing Software Development Engineer, TensorRT-LLM

Senior System Software Engineer, Automotive Performance

Engineering Manager, Deep Learning Inference

Senior AI Systems and Algorithms Engineer

Software Engineer, CUDA Deep Learning Systems

Senior Software Engineer, CUDA Deep Learning Systems