NVIDIA

Full-stack Engineer

• Develop and verify GPU features from initial design through deployment, collaborating globally with hardware and software teams to deliver world-class products
• Develop and lead the integration of complex system software components, collaborating across hardware and software teams to deliver robust, high-performance GPU and embedded system solutions
• Help design and implement features for our GPUs; working with software and hardware engineering teams
• Evaluate, recommend, and develop methodologies and tools to measure and enhance security and quality of embedded and system software
• Identify vulnerabilities in our production kernel and embedded software, building proof of concepts, and working with teams to address them
• Have opportunities to collaborate and communicate effectively with teams from all around the globe

System Software Engineer, GPU Kernel Driver

Product Manager

• Define, own, and drive the strategy enabling the world’s enterprises to adopt accelerated query engines powered by NVIDIA’s platform
• Engage deeply with customers, ISVs, storage partners, and CSPs to find opportunities to improve their experience, owning the voice of the customer and incorporating insights into hardware and software roadmaps and priorities
• Collaboratively develop and lead enterprise go-to-market motions, working with a cross-functional team on asset creation, market research, positioning, enablement, etc.
• Track and act on important measures for adoption, engagement, and customer success to continuously improve our value proposition and developer experience
• Serve as the point person for presenting vision, opportunities, and progress, setting expectations and managing internal and external collaborators

Senior Product Manager – Structured Data Query Engines

• Design, build, and optimize containerized inference execution for the latest 3D VLMs from NVIDIA, turning research work into production-grade, highly optimized software (NIMs, NVIDIA Inference Microservices)
• Develop benchmarks to validate the models accuracy and performance (latency, throughput, scalability)
• Release and maintain the models and their pipelines throughout their lifecycle (bug fixes, security patches)
• Contribute VLM-related features to Open-Source projects like vLLM
• Collaborate closely with Research and Product teams and influence our common roadmaps

Senior Software Engineer – VLM Microservices, Neural Reconstruction

Architect

• Architecting and maintaining custom profiling frameworks that provide a unified view of execution across CPU (multi-core/multi-socket) and GPU (multi-node/NVLink) environments.
• Conducting deep-dive benchmarking of EDA applications to characterize memory access patterns, cache hit rates, and instruction-level parallelism.
• Using GPU profilers to detect GPU-side inefficiencies such as warp divergence, sub-optimal occupancy, and PCIe/NVLink bottlenecks.
• Developing tools to monitor and attribute high-watermark memory usage in multi-terabyte EDA builds, finding opportunities for data structure compression or smarter memory pooling.
• Developing predictive models to guide hardware procurement and cloud instance selection based on built gate-count and algorithmic complexity.

Senior Performance Architect – Heterogeneous Workload Optimization

Mechanical Engineer

• Analyze the architectural requirements, perform the trade-off analysis for implementation, and deliver high performance, area and power efficient RTL Blocks
• Craft micro-architecture specification, implement in high-quality RTL, and deliver a fully verified, synthesis and timing clean block
• Collaborate with chip architects, verification engineers, formal verification engineers, and SoC integration engineers in order to meet the goals of the block in a timely manner
• Identify potential IP solutions for specific use cases and assist in selecting, customizing and integrating the right IP solutions

Principal Digital Design Engineer

• Develop and evolve a state-of-the-art inference framework in modern C++ that extends TensorRT with autoregressive model serving capabilities, including speculative decoding, LoRA, MoE, and KV cache management.
• Design and implement compiler and runtime optimizations tailored for transformer-based models running on constrained, real-time platforms.
• Collaborate with teams across CUDA, kernel libraries, compilers, and robotics to deliver high-performance, production-ready solutions.
• Contribute to CUDA kernel and operator development for critical transformer components such as attention, GEMM, and MoE.
• Benchmark, profile, and optimize inference performance across diverse embedded and automotive environments.
• Stay ahead of the rapidly evolving LLM/VLM ecosystem and bring emerging techniques into product-grade software.

Senior Software Engineer – TensorRT, Edge-LLM

• Managing an AI networking ecosystem platform through the complete life cycle from business strategy to R&D tradeoffs to go-to-market
• Defining use cases, examples, and tools to craft and convey the product value proposition
• Collecting requirements to define future products, including competitive analysis and customer feedback
• Working closely with partners to ensure products get to market on time

Senior Product Manager – AI Networking

Account Manager

• Lead the end‑to‑end account strategy for RTX, focusing on modeling & simulation, CAE/CFD, sensor processing, AI/ML, and physical AI workflows.
• Developing strong executive relationships while engaging deeply with engineers, architects, and developers to understand challenges and identify performance‑enhancing opportunities.
• Identify integration opportunities for NVIDIA’s libraries and SDKs (CUDA, Triton, TensorRT , cuSignal , NeMo , Omniverse) to accelerate key workloads.
• Champion adoption of NVIDIA technologies—guiding evaluations, POCs, design decisions, and scale‑out phases.
• Implement NVIDIA’s ecosystem‑led GTM, aligning ISVs, CSPs, and OEMs to speed up prototyping, deployment, and customer outcomes.
• Collaborate with NVIDIA solution architects, product, engineering, and partner teams with a low ego, one‑team approach.

Senior Account Manager

Security Engineer

• Understand and analyze the potential vulnerabilities and risks in future systems for AI and AI-based systems.
• Develop creative hardware, software, and algorithms to enable trustworthy AI systems with strong and verifiable security, privacy, and safety guarantees.
• Collaborate with a diverse set of teams across the company, spanning software, hardware, research, and product groups.
• Publish original research and speak at conferences and events.

Research Scientist, Security and Privacy

Backend Engineer

• Research, prototype, develop and optimize solutions, tools and libraries for deep learning, data analytics, machine learning, or scientific computing
• Analyse, influence and improve deep learning libraries and frameworks standards and APIs according to good engineering practices
• Collaborate with team members and other partners.

System Software Engineer, Python, C/C++, Deep Learning

Manager

• Research AI legislation and policy developments to stay abreast of regulatory changes and industry trends that may impact NVIDIA's government affairs initiatives
• Manage industry affiliations such as trade associations, monitoring relevant output and ensuring the team is informed about relevant publications and activities
• Analyse proposed regulations and policy frameworks to assess their potential implications for NVIDIA's products, services, and market positioning
• Assist in the development and execution of strategic programs aimed at fostering positive relationships with EU institutions
• Provide comprehensive administrative support to the team, including scheduling meetings, preparing materials, and managing correspondence
• Serve as a primary point of contact for logistics-related inquiries and collaborate with internal and external stakeholders
• Assist in budget planning and management for government affairs programs, ensuring adherence to financial guidelines and cost-effective resource utilisation
• Find opportunities for process improvement and operational efficiency within the Government Affairs Team, including helping to identify how the team can implement AI tools in their work
• Coordinate logistical aspects of the EU programs, including meetings, events, conferences, and site visits

Government Affairs Manager

Machine Learning Engineer

• Improve inference speed for Cosmos WFMs on GPU platforms.
• Effectively carry out the production deployment of Cosmos WFMs.
• Profile and analyze deep learning workloads to identify and remove bottlenecks.

Senior Deep Learning Engineer

Software Engineer

• Research and develop cutting-edge techniques in deep learning, machine learning, HPC (High Performance Computing), graphs and data analytics
• 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

Developer Technology Engineer – AI

• Spearhead innovation to architect and deliver highly reliable, performant, and scalable cloud-native systems.
• Lead the design and development of next-generation microservices and distributed systems with a strong emphasis on performance optimization and cost efficiency.
• Define and evolve system architecture strategies, ensuring alignment with long-term business and technical goals.
• Tackle complex challenges in job orchestration, resource optimization, and self-healing infrastructure with a focus on automation and resilience.
• Build and scale end-to-end observability solutions including metrics pipelines, alerting frameworks, and telemetry storage.
• Leverage data analytics and predictive modeling to proactively improve system behavior and reliability.
• Provide technical leadership and mentorship across teams while collaborating cross-functionally with product, infrastructure, and operations groups to drive strategic initiatives and foster a culture of engineering excellence and continuous improvement.
• Design and operate massively scalable systems—handling thousands to millions of jobs and servers—using deep expertise in Kubernetes and public cloud platforms (AWS, Azure, GCP).

Senior System Software Engineer

• Architecting GPU power features and system level power management solutions for NVIDIA products
• Collaborate closely with other Architects, Software Engineers, ASIC Design Engineers, and Product teams
• Study, devise and implement power management strategy for NVIDIA's GPU roadmap
• Research and develop solutions to address complex energy efficiency problems
• Deploy machine learning techniques to develop highly accurate power and performance models of our GPUs and platforms