Latest Research Jobs

Relational Foundation Model Engineer, Modern Data Stack

Design and develop novel Transformer and GNN-based foundation models that generalize across relational databases and heterogeneous graphs. Work across the full ML lifecycle—from architecture design to inference optimization—on real-world applications like fraud detection, forecasting, and recommendation systems. Collaborate with researchers and engineers to build a unified AI model for enterprise data.

NVIDIA Germany

On-site Permanent

Graduate Physicist

This role involves tackling diverse technical challenges across healthcare, defence, and energy sectors by applying physics-based problem solving to real-world engineering projects. You'll work on cutting-edge systems such as holographic imaging, ultrasonic measurement, and magnetic positioning, combining lab work with simulation and analysis. The position emphasizes rapid learning, innovation, and collaboration within a supportive, R&D-driven environment.

Cambridge Consultants United Kingdom

On-site Permanent Clearance Required

Compiler Engineer - AI Inference

Develop and optimize compilers for AI inference workloads on NVIDIA's next-generation GPUs, focusing on kernel generation, computational graph optimizations, and hardware-software co-design. Collaborate with cross-functional teams to advance compiler frameworks and enable high-performance AI deployment at scale. Work spans MLIR-based tooling, deep learning performance, and datacenter-scale optimization.

NVIDIA Cambridge, United Kingdom

Graduate AI and Secure Technologies Engineer (2026 start)

Work on cutting-edge security and AI engineering challenges across critical infrastructure, defence, and emerging technologies. Contribute to threat modelling, secure-by-design architectures, vulnerability analysis, and security assurance in multidisciplinary teams. Engage in full lifecycle engineering from concept to deployment, with opportunities to interact directly with clients and develop technical prototypes.

Cambridge Consultants United Kingdom

Relational Foundation Model Engineer, Modern Data Stack

Design and develop novel Transformer and GNN-based foundation models that generalize across relational databases and heterogeneous graphs. Work across the full ML lifecycle—from architecture design to inference optimization—on a unified model powering enterprise AI applications in forecasting, fraud detection, and recommendations. Collaborate with researchers to advance relational reasoning and deploy cutting-edge systems into production.

NVIDIA

Relational Foundation Model Engineer, Modern Data Stack

Design and develop novel Transformer and Graph Neural Network (GNN) architectures that generalize across relational databases and heterogeneous graphs. Work across the full ML lifecycle—from model design and large-scale training to optimization and inference acceleration—targeting real-world enterprise applications like fraud detection, forecasting, and recommendation systems. Collaborate with researchers to advance foundational AI models that redefine the modern data stack.

NVIDIA

Relational Foundation Model Engineer, Modern Data Stack

Design and develop novel Transformer and GNN architectures for a unified foundation model that understands relational databases and heterogeneous graphs. Work across the full ML lifecycle—from research to production deployment—on applications like fraud detection, forecasting, and recommendation systems. Collaborate with researchers to push the boundaries of relational reasoning in enterprise AI.

NVIDIA

Relational Foundation Model Engineer, Modern Data Stack

Design and develop novel Transformer and GNN architectures for a unified foundation model that interprets relational databases and heterogeneous graphs. Work across the full ML lifecycle—from architecture design to inference optimization—on high-impact applications like fraud detection, forecasting, and recommendation systems. Collaborate with researchers to advance graph learning and relational reasoning in enterprise AI.

NVIDIA

Compiler Engineer - AI Inference

This role involves developing advanced compiler technologies for AI inference and training workloads, focusing on kernel generation and computational graph optimizations tailored to NVIDIA's GPUs. You'll work at the intersection of hardware and software, collaborating with experts to co-design future silicon and optimize datacenter-scale AI deployments. The position demands deep expertise in compiler design, MLIR, and performance optimization in high-performance computing environments.

NVIDIA United Kingdom

Senior Solutions Architect – Large Scale Neural Networks Inference

Lead technical strategy for AI inference across EMEA by collaborating with AI-native customers and internal teams to solve challenges in latency, efficiency, and scalability. Design and optimize high-performance inference pipelines using NVIDIA's stack, including TensorRT-LLM and Dynamo, and translate real-world deployment insights into product improvements. Work at the intersection of research and engineering to advance large-scale neural network inference in production environments.

NVIDIA France

Solutions Architect, CSP GTM

Design and demonstrate GPU-accelerated solutions leveraging NVIDIA and GCP technologies for generative AI and machine learning workloads. Collaborate with developers, data scientists, and technical leaders to optimize training and inference pipelines on hyperscaler infrastructure. Act as a technical bridge between NVIDIA, Google Cloud, and enterprise customers to drive adoption of accelerated computing in AI.

NVIDIA Reading, United Kingdom

Solutions Architect, CSP GTM

This role involves designing and demonstrating GPU-accelerated solutions for Generative AI and machine learning workloads on hyperscaler platforms, with a primary focus on Google Cloud (GCP). The Solutions Architect will collaborate with NVIDIA’s partners and customers to optimize training and inference pipelines, provide technical leadership, and translate developer needs into product improvements. It emphasizes deep technical engagement across engineering, product, and sales teams to drive adoption of NVIDIA’s AI platforms.

NVIDIA France

Graduate AI and Secure Technologies Engineer (2027 start)

This role involves working on real-world engineering challenges in cyber security, AI, embedded systems, and connected technologies. You'll contribute to threat modelling, security risk assessments, and secure-by-design system architectures, collaborating with multidisciplinary teams on projects across various sectors including defence, industrial systems, and critical infrastructure.

Cambridge Consultants United Kingdom

On-site Permanent Clearance Required