NVIDIA

Full-stack 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

Product Manager

• 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

Architect

• 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

Power Architect

Designer

•Verify the design and implementation of inference accelerator
•Responsible for verification of the ASIC design, architecture, reference models and micro-architecture using advanced verification methodologies
•Understand the design and implementation of your unit, define the verification scope, develop the verification infrastructure and verify the correctness of the design
•Collaborate with architects, designers, and pre and post silicon verification teams to accomplish your tasks
•Implement and optimize automated verification flows to improve productivity and efficiency
•Stay updated on the latest trends and advancements in ASIC design verification and incorporate innovative techniques into the verification process

Senior ASIC Design Verification Engineer

Systems Engineer

• Build and develop power delivery systems for data center and super compute platforms, including multiphase VRMs and Intermediate Bus Converters (IBCs).
• Architect low voltage, high current (500A-1000A+) power rails for LPU, GPU and accelerator modules.
• Apply control theory principles to optimize power converter performance, stability, and transient response.
• Select and characterize power components including MOSFETs, inductors, transformers, and magnetic devices using vendor tools and configuration GUIs.
• Collaborate with ASIC and package teams to ensure power integrity across high-density PCB builds.
• Develop and complete lab validation plans using oscilloscopes and other test equipment.
• Build automation scripts to improve characterization efficiency and data analysis.
• Collaborate with power management ICs via I2C, SPI, and PCIe protocols for system integration and debug.
• Work with cross-functional teams including mechanical, thermal, firmware, and silicon build engineers.

Senior Power System Engineer

Engineer

• Verify the design and implementation of the industry's leading GPUs.
• Verify the micro-architecture using formal verification tools, define the verification scope, and ensure design correctness.
• Employ advanced formal techniques to obtain sufficiently bounded proofs while working with architects, designers, and pre- & post-silicon verification teams.
• Efficiently execute the formal verification effort for the entire project cycle, delivering high-quality results on schedule.
• Clearly convey those results to the team.
• Identify key behaviors for verification to write clear testplans for complex designs.
• Execute testplans using the latest formal techniques, including the development of environment assumptions, assertions and cover properties.
• Develop abstraction models to overcome complexity challenges and obtain full proofs, or bounded proofs with sufficient coverage.
• Debug RTL to identify causes of failure scenarios.
• Contribute to flow and script development to improve team efficiency.
• Articulate formal verification coverage of the design to partners.

Formal Verification Engineer, New College Grad

• Lead multiple teams responsible for CI/CD platforms and cloud operations that support GPU-accelerated, microservice-based Omniverse workloads.
• Drive the build, evolution, and operation of end-to-end CI/CD systems, including build pipelines, automated testing, deployment workflows, and release management.
• Coordinate cloud infrastructure used by Omniverse services, spanning compute, networking, storage, security, and control-plane components at global scale.
• Partner closely with software engineering, SRE, and product teams to align development workflows, operational requirements, and delivery timelines.
• Guide the development of tooling and services that improve rollout safety, observability, monitoring, and lifecycle management of distributed systems.
• Evaluate new technologies in CI/CD, cloud platforms, and GPU compute, introducing improvements that raise reliability, efficiency, and developer productivity.
• Establish strong operational practices, including incident readiness, postmortems, and continuous improvement across owned systems.

Senior Manager, Omniverse DevInfra CI/CD

DevOps Engineer

• Build and operate highly reliable, scalable CI/CD pipelines based on GitLab and Github, as well as maintain developer R&D environments using virtualized GPU desktop instances for Omniverse and Isaac development environments, across production, staging, and dev systems
• Support orchestration of GPU‑enabled clusters running Linux and Windows workloads using containerization tools (Docker, Kubernetes) and virtualization (VMware, KVM).
• Automate infrastructure provisioning, scaling, and configuration using Infrastructure‑as‑Code (Terraform, Ansible, AWS CDK, Azure Bicep, etc.).
• Monitor and optimize system health, performance, build/test throughput, and pipeline reliability.
• Collaborate closely with Omniverse and Isaac developer teams to smooth release workflows, increase velocity, and code quality.
• Mentor and guide junior team members; lead by example in DevOps protocols.