Senior Hpc Ai Cluster Engineer jobs at Nvidia in United Kingdom, Southampton

What you'll be doing:

• Research novel AI techniques to secure next-generation networks and apply them to existing NVIDIA products.

• Investigate and analyze network telemetry for indicators of vulnerabilities in secure environments.

• Collaborate with NVIDIA researchers to explore innovative ways to improve security in networking products.

• Contribute to projects that have potential real-world impact on NVIDIA's product portfolio.

What we need to see:

• Holding a PhD or MSc or equivalent experience in Electrical Engineering, Computer Science, or a related field with a focus on AI.

• 5+ years of relevant experience.

• Experience with innovative AI tools, frameworks, and methods related to cybersecurity incident detection and prevention.

• Background in cybersecurity, networking (TCP/IP), and network security (TLS/IPSec).

• Solid programming skills and a deep understanding of secure system design.

Ways to stand out from the crowd:

• PhD with a track record of publication in top peer-reviewed AI conferences or equivalent experience leading AI projects.

• Expertise with LLMs and recent advancements in neural networks.

• Architectural knowledge of system security.

• Understanding of common attack vectors targeting network devices and methods to mitigate them.

• A proven track record to translate sophisticated research into practical solutions.

• Research formal verification methods to prove the safety of security and communication protocols.

• Collaborate across the networking organization to use formal methods for improving the security of network cards, switches, and DPUs, working with hardware, software, research, and product teams.

• Research, design, develop, and implement architecture solutions for integrating formal verification for security features into networking products.

• Architectural modeling and validation, following standards bodies.

• Work with customers and partners to identify and address security issues and threats.

• BSc, MS, or PhD in Electrical Engineering, Computer Science, or Computer Engineering, or equivalent experience.

• 5+ years of proven experience.

• Background in formal verification methods, in at least one of the following: model writing, bounded and unbounded model checking, and symbolic execution.

• Programming and debugging fundamentals across languages such as Python, ARM assembly, and C/C++.

• The ideal candidate will enjoy working in a diverse team, with excellent communication skills and a genuine passion for teamwork.

• Proven track record of leading features across teams.

• Solid programming skills and a deep understanding of secure system building.

• Background in high-bandwidth networking protocols such as RDMA.

• Experience in PCIe devices and switches.

• Background in system security, including Linux security features and confidential computing.

• Experience in TLA+

What You'll Be Doing:

• Support developers in your ISV segment as a technical consultant, resolving issues and promoting NVIDIA technology adoption.

• Accelerate critical workloads by demonstrating ground breaking solutions that integrate the core NVIDIA stack into developer products, platforms, and pipelines.

• Advise on the technical enablement resources—such as sample code, guides, demonstration pipelines, and tools to highlight the application of technologies in solving real-world problems

• Guide partners and startups through onboarding and integration with NVIDIA’s programs, fostering co-innovation and the development of next-generation solutions.

• Map, track, and supervise the developer ecosystem to identify growth opportunities, inform technology roadmaps, and shape adoption strategies.

• Collaborate multi-functionally with solution architects, engineering, product management, and marketing to drive developer engagement and optimize partner adoption strategies.

• Collaborate with partner engineering teams, technical leaders, and decision-makers to identify objectives, address technical hurdles, and promote guidelines for successful integrations.

• Represent and advocate for the partner technical needs and feedback to NVIDIA’s internal product and engineering teams, supplying actionable insights from field deployments to influence product roadmaps.

What We Need to See:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience).

• A minimum of 8-10+ years of overall professional experience in the technology industry in software engineering, developer relations, technical partnerships, or customer-facing technical roles including 5+ years of direct hands-on experience working with software & technology companies in EMEA

• Proven experience leading, partnering, and scaling developer programs at major technology companies, ISVs, or within relevant verticals.

• Significant technical proficiency in high-performance computing, cloud, AI/ML, and/or vertical-specific frameworks and libraries.

• Excellent interpersonal skills with the ability to distill complex technical concepts for diverse technical and non-technical audiences from engineers to executives.

• Experience leading technical collaborations with engineering and product teams - including architectural design, code reviews, technical mentorship, and delivery of technical talks or workshops

• Skilled in coordinating complex technical projects, addressing needs, prioritizing concerns, and collaborating with various teams.

• Commercialproficiency/experience:

Ways to Stand Out from the Crowd:

• Hands-on experience building or optimizing vertical-specific solutions (e.g., network stacks, bidding algorithms, data pipelines, etc.).

• Familiarity with advanced computing, AI, and/or GPU acceleration platforms such as CUDA, Triton, NeMo

• Track record in crafting and implementing systems for real-time processing and low-latency decision-making.

• Experience working in customer-facing technical roles focused on technical evaluation and product integration

• Background in developing product partnerships and executing GTM strategies with externalorganizations/partnersas well as experience working with developers building AI-embedded products serving one of the following industries: Healthcare & Life Sciences, Financial Services, Automotive, Manufacturing, or Retail

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people.

What will you be doing:

• You will bring together and understand internal and external customer requirements to improve AI cluster resiliency and design AIOps-based solutions that address these needs.

• develop automated workflows for issue detection and root cause analysis and closely collaborate with operators to debug sophisticated, full-stack AI cluster problems. We will bring to bear the findings for product improvements!

• deliver compelling technical presentations and lead hands-on demos or training. You'll also handle evaluation deployments (POC/POV) and ensure smooth, reliable installations by staying engaged and encouraging throughout the customer journey.

What we need to see:

• Bachelor of Science or equivalent experience

• 12+ years of networking experience in enterprise or service provider environments, with strong hands-on expertise in routing and switching.

• Proficient in scripting and automation using Python or similar languages, with strong Linux expertise.

• Proven experience working directly with customers to resolve issues and ensure success in Systems Engineer or SRE roles.

• Exceptional oral, written, and presentation skills for clearly communicating complex technical topics.

• Demonstrated ability to collaborate effectively across teams, partnering with operations, engineering, and product development

Ways to stand out from the crowd:

• Experience with data center infrastructure and cloud architectures

• Background in network performance monitoring or observability

• Previous experience working at a technological start-up

For two decades, we have pioneered visual computing, the art and science of computer graphics. With our invention of the GPU - the engine of modern visual computing - the field has expanded to encompass video games, movie production, product design, medical diagnosis and scientific research. Today, we stand at the beginning of the next era, the AI computing era, ignited by a new computing model, GPU deep learning. This new model - where deep neural networks are trained to recognize patterns from massive amounts of data - has shown to be deeply effective at solving some of the most complex problems in everyday life.

NVIDIA runs one of the largest Perforce installations in the world, and a very large Git installation as well. Our Software Configuration Management (SCM) Tools and Infrastructure group is looking for a top SCM architect. You will tackle the challenges that we face with operating at scale to produce a best-in-industry solution and enable us to continue to provide unprecedented performance and reliability for our users. You will work in our team to engineer new solutions to scale our Perforce and Git infrastructure to handle large and ever-growing load and data volume. You will design and code processes and automation tools to improve productivity managing and administering the SCM systems and applications used by our globally distributed engineering teams.

What you'll be doing:

• Responsible for the full SCM environment including application, OS, and server hardware components, developing the continued automation and innovation needed for our large environment

• Create new solutions to improve the reliability and performance of our ever-growing infrastructure, and work with automated orchestration tools to deploy those improvements to hundreds of systems worldwide

• Be part of a global team and will evaluate technology alternatives, work closely with other project members to specify solutions, craft schedules, and lead ongoing enhancements and support

• Learn and greatly improve the daily productivity of the world’s top chip designers and software engineers

What we need to see:

• MS (preferred) or BS in Computer Science (or equivalent experience) or a related field with at least 3+ years of experience

• Deep understanding of Software Configuration Management (SCM) processes and tools such as Perforce, Git, Subversion, or ClearCase for large, multi-site development

• You've configured/deployed Continuous Integration (CI) and Continuous Deployment (CD) systems in your past experience

• Excellent interpreted language skills highly desired – Object Oriented Perl or Python preferred and Strong software engineering process skills required

• Strong object-oriented programming and design pattern knowledge and background - Object Oriented Perl, Python, C++, or Java preferred

• Experience with databases, MySQL or Postgres preferred, experience with NoSQL databases a plus

• Experience with DevOps or system administration with Linux systems required (CentOS/RHEL and Ubuntu preferred)

• Strong experience with automation required, Ansible or Puppet preferred and Excellent interpersonal skills, including written and verbal communication

• You are comfortable and enjoy working with dynamic and ever evolving environments

Ways to stand out from the crowd:

• Meticulous organizer with an ever positive, can-do attitude

• Demonstrate use of out-of-box thinking for creative solutions to highly sticky problems

• Fun and enthusiastic teammate who enjoys a challenge and celebrates success

• Collaborating with NVIDIA’s training framework developers and product teams to stay ahead of the latest features and help partners to adopt them effectively.

• Assisting with deployment, debugging, and improving the efficiency of AI workloads on extensive NVIDIA platforms.

• Benchmarking new framework features, analyzing performance, and sharing actionable insights with both customers and internal teams.

• Working directly with external customers to solve cluster performance and stability issues, identify bottlenecks, and implement effective solutions.

• Build expertise and guide customers in scaling workloads efficiently and reliably on the latest generation of NVIDIA GPUs.

• Contributing to Europe’s Sovereign AI initiative by helping customers implement advanced resiliency features within AI training pipelines.

• BS, MS, PhD or equivalent experience in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or a related engineering field—or equivalent practical experience.

• 8+ years of experience in accelerated computing technologies at cluster scale, ideally including work with NVIDIA platforms.

• Strong programming skills in at least one of the following languages: C, C++, or Python.

• Practical experience identifying and resolving bottlenecks in large-scale training workloads or parallel applications.

• Hands-on experienced in profiling and debugging large parallel applications.

• Solid understanding of CPU and GPU architectures, CUDA, parallel filesystems, and high-speed interconnects.

• Experienced in working with large compute clusters with an understanding of their internal scheduling and resource management mechanisms (e.g. SLURM or Cloud based clusters).

• Proficient knowledge of training pipelines and frameworks, encompassing their internal operations and performance attributes.

• Experience in debugging training pipelines running on thousands of GPUs in production environment.

• Hands-on experience with performance profiling and optimizations using tools like Nsight Systems, Nsight Compute and good understanding of NCCL, MPI and low-level communication libraries.

• Ability to debug stability issues across the entire stack: parallel application, training frameworks, runtime libraries, schedulers, and hardware.

• Solid understanding of the internal workings of LLM frameworks such as PyTorch, Megatron-LM, or NeMo, and how they affect compute layers like CPUs, GPUs, network and storage or understanding of inference tools such as vLLM, Dynamo, TensorRT-LLM, RedHat Inference Server or SGLang.