Senior Solutions Architect Supercomputing jobs at Nvidia in United Kingdom, Southampton

• Serve as the primary technical expert between NVIDIA and our customers, understanding their technology and provide the best AI solutions/ guidance on training process in terms of tools and methodology

• Build proof-of-concepts and demonstrations that highlight the power of NVIDIA AI platforms in robotics

• Partner with developers, researchers, technology specialists, IT professionals, and executives to facilitate the integration of NVIDIA technology

• Work with Engineering, Product and Sales teams to develop, plan best suitable solutions for customers. Enable development and growth of product features through customer feedback and proof-of-concept evaluations.

• MS/PhD or equivalent experience in Computer Science, Data Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering fields.

• Deep expertise in AI/Deep Learning, with hands-on experience in training or optimizing VLMs for production

• Expertise with deep learning frameworks for training VLMs (PyTorch, Nemo), and/or experience with such model's optimization methods and tools (TensorRT and Triton Inference Server).

• Excellent verbal, written communication, and technical presentation skills in English.

• 5+ years' work or research experience with Python/ C++ / other software development

• AI passionate with a growth mindset, ability to collaborate effectively with different teams (Engineering, Product, Sales, Marketing) in a rapid evolving environment while continuously learning and sharing insights.

• Familiarity with Cosmos (e.g. Cosmos-Reason) and Isaac GR00T family of models.

• Familiarity with robotics simulation environments (Isaac Sim, Isaac Lab, MuJoco, etc.).

• Experience in large scale training / understanding of modern model, data, expert, context parallel training techniques.

• Track record in Neural Networks inference optimization for Physical AI use cases

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

What you'll be doing:

• Work with financial institutions and their technology ecosystem in leveraging NVIDIA's advanced technologies

• Provide technical guidance and support to internal teams and external stakeholders, ensuring effective ideation, research and developing solution prototypes, followed by a successful deployment.

• Work closely with product management, engineering, applied research and sales teams to develop and deliver comprehensive solutions.

• Stay updated on industry trends and advancements in hardware technologies to continually improve and innovate NVIDIA's software and data center solutions.

What we need to see:

• BS/MS/PhD degree in Machine Learning, Computer Science, or related technical field.

• Minimum of 5 years of experience in AI and accelerated technologies.

• Background working within Financial Services firms.

• Expertise in writing code for training and/or inference for NVIDIA GPUs.

• Capable of working in a constantly evolving environment without losing focus.

• Self-starter with a passion for continuous learning and sharing findings across the team.

Ways to stand out from the crowd:

• Demonstrated understanding of how GPU acceleration can be applied to financial workloads.

• Knowledge of software-defined infrastructure and orchestration tools (Kubernetes, OpenStack).

• Proficiency in cloud platforms (AWS, Azure, Google Cloud) and hybrid cloud solutions.

• Understanding of HPC systems: data center design, high speed interconnect InfiniBand, Cluster Storage and Scheduling related design and/or management experience.

• 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.