Lead business development and delivery for AI-driven simulation software within aerospace and defense, driving customer acquisition, shaping go-to-market strategy, and managing technical execution. Engage with senior engineering leaders, scope and deliver high-impact projects, and translate customer needs into product evolution. This hybrid role blends strategic sales with hands-on technical leadership and regular travel to customer sites.
This role involves building and running high-fidelity CFD simulations from geometry preparation to post-processing for moderately complex engineering cases. You'll work at the intersection of CAE and data science, supporting the development of AI-driven simulation models and contributing to automated workflows on cloud and HPC platforms. The position includes customer collaboration, model adaptation for deep learning surrogates, and occasional international travel to support on-site engagements.
A Data Scientist in the Delivery team will work closely with Simulation and Machine Learning Engineers to transform AI models into practical engineering tools. You'll preprocess and analyze complex data, build deep learning models combined with optimization methods, and develop scalable data pipelines for production. The role involves direct collaboration with customers across industries like Aerospace, Energy, and Semiconductors, including on-site work globally, ensuring seamless integration of data science solutions with physics-based simulations.
This role focuses on growing NVIDIA's developer ecosystem in manufacturing by supporting developers, ISVs, startups, and enterprises across EMEA. You'll design technical enablement materials, guide integration of NVIDIA platforms, and act as a bridge between the manufacturing community and internal engineering teams. The position emphasizes real-world AI applications such as robotics, digital twins, and computer vision in industrial settings.
This role focuses on growing NVIDIA's developer ecosystem in the manufacturing sector by enabling developers, ISVs, startups, and system integrators to adopt NVIDIA’s AI and accelerated computing platforms. The individual will design technical enablement materials, support solution integration, and act as a bridge between the manufacturing developer community and internal engineering and product teams. Key use cases include robotics, digital twins, simulation, computer vision, and predictive maintenance in industrial environments.
This role involves engaging with developers, software vendors, and industrial enterprises across EMEA to drive adoption of NVIDIA’s AI and accelerated computing platforms in manufacturing. You'll design technical enablement materials, support partners in integrating NVIDIA technologies, and act as a bridge between the developer community and internal engineering teams. The position focuses on use cases like robotics, digital twins, computer vision, and predictive maintenance in industrial environments.
This role involves engaging with developers, software vendors, and industrial enterprises across EMEA to drive adoption of NVIDIA's AI and accelerated computing platforms in manufacturing. The individual will develop technical content, deliver workshops, and support partners in implementing solutions for robotics, digital twins, simulation, and industrial AI. They will also act as a bridge between the developer community and NVIDIA's engineering teams to influence product development.
This role involves driving adoption of NVIDIA's AI and accelerated computing platforms within the manufacturing sector across EMEA. You'll work directly with developers, ISVs, startups, and industrial enterprises to build solutions in robotics, digital twins, computer vision, and predictive maintenance. The position focuses on technical enablement through workshops, reference architectures, and co-innovation, while bridging developer feedback to internal product and engineering teams.
This role involves designing, building, and deploying advanced machine learning models to solve complex operational challenges in real-world environments. You will work closely with a high-calibre founding team, industrial data, and customer environments to take machine learning systems from early validation through to scalable deployment.
The role involves software testing, software releases, and customer support for an AI startup. You will work with Python, Bash, Linux, Docker, and AWS, and have the opportunity to develop skills in automation, cloud, and edge technologies in a fast-moving, collaborative environment.
As a Senior CFD Engineer, you will work closely with Data Scientists and Machine Learning Engineers to deliver high-fidelity simulations and address complex engineering challenges. Your role involves building multi-physics models, automating simulation pipelines, and collaborating with customers to integrate AI-driven solutions, while traveling globally to support on-site projects.
This role involves deploying and scaling machine learning models for high-fidelity engineering simulations, working directly with customers to integrate AI into production environments. The Principal ML Engineer will lead technical architecture, build robust data and inference pipelines using Python, PyTorch, and Kubeflow, and mentor teams across global customer sites. The position bridges advanced physics-based challenges with practical AI solutions in industries like aerospace, energy, and semiconductors.
This role involves building and deploying AI-driven simulation applications that solve complex engineering problems across industries like aerospace, energy, and semiconductors. You'll work closely with customers, data scientists, and ML engineers to design end-to-end tools that integrate physics AI models into real-world engineering workflows. The position emphasizes rapid prototyping, full-stack development, and translating cross-industry challenges into scalable software solutions.
Design and build full-stack internal tools and platforms that empower non-technical users by identifying patterns in workflows and abstracting them into reusable systems. Work closely with stakeholders to define priorities, iterate on feedback, and ship features that drive autonomy across the organization. Use Python, TypeScript, and React in a high-impact, collaborative environment focused on AI safety and reliability.
This role involves designing and maintaining large-scale continuous integration infrastructure to support rapid, reliable code deployment across multiple cloud environments. The engineer will build intelligent test selection systems, improve CI reliability through flake detection and automation, and enhance developer productivity with scalable tooling. The position operates within a high-impact research and product environment focused on safe and steerable AI systems.
