Design and build end-to-end applications that integrate AI-driven physics models into real-world engineering workflows. Collaborate with customers and technical teams to prototype, deploy, and iterate tools that solve complex engineering challenges across industries like aerospace, energy, and semiconductors. Work across the full stack with a focus on backend services, cloud infrastructure, and customer-driven product development.
A Forward Deployed Software Engineer at PhysicsX works directly with customers and engineering teams to build and deploy AI-driven simulation applications that solve complex engineering problems across industries like aerospace, energy, and semiconductors. The role involves full-stack development, rapid prototyping, and on-site collaboration, with a focus on delivering production-grade tools using physics AI models. Engineers contribute to backend services, APIs, and platform features while shaping product direction based on real-world customer needs.
A Senior AI Engineer role leading the design and implementation of AI/ML solutions within a global law firm's technology team. The position involves technical leadership, managing internal and external teams, and driving the AI platform strategy from development to deployment. The role focuses on delivering scalable, production-grade AI systems integrated with enterprise architecture while mentoring engineers and aligning with business outcomes.
This role involves leading the technical strategy and implementation of AI and machine learning solutions across a global legal firm. The Senior AI Engineer will manage a team of IT professionals, oversee full lifecycle AI development, and integrate AI systems with scalable architecture. They will collaborate with senior stakeholders to align AI use cases with business outcomes and drive innovation through continuous improvement and third-party vendor management.
Design and maintain large-scale HPC/AI clusters with a focus on automation, monitoring, and performance optimization across bare metal, OS, and application layers. Develop CI/CD pipelines and self-service tooling for infrastructure management, supporting cutting-edge research and development in AI and accelerated computing. Collaborate with specialists in GPU compute, networking, and storage to deploy and troubleshoot high-performance systems at scale.
This role involves designing, implementing, and maintaining large-scale HPC/AI clusters, managing job/workload schedules, and developing CI/CD pipelines. You will work closely with HPC, OS, GPU compute, and systems specialists to architect and optimize performance platforms, and support R&D activities.
This role involves designing, building, and enhancing high-impact trading and research platforms in a fast-moving, highly technical environment. You will work closely with quants, traders, and the CTO, contributing to core trading systems, front-office tooling, and data-driven applications using C# and .NET.
This role involves leading the architectural evolution and scaling of a high-throughput platform for a global financial institution. Responsibilities include influencing system design, driving automation, and optimizing performance for a platform processing millions of complex operations monthly.
Design and build full-stack AI-powered applications, translating machine learning outputs into production-ready systems. Collaborate with data scientists and product managers to deliver scalable, user-centric solutions for global clients in regulated industries. Focus on robust architecture, cloud deployment, and client-facing technical leadership.
This role involves designing and maintaining the MLOps and deployment infrastructure that enables data scientists to transition machine learning models from exploration to production. The engineer will work across AWS, Azure, and GCP to build scalable, containerised systems using Kubernetes and infrastructure-as-code tools. The focus is on creating reliable, secure, and high-performance platforms that support client-facing AI solutions.
This role involves leading the design and implementation of advanced algorithms for intelligent systems in defence and security contexts, with a focus on machine learning, AI, and sensor processing. You'll act as technical architect on complex projects, mentor engineers, and contribute to client-facing proposals and sales efforts. The position requires security clearance and combines hands-on development with strategic technical leadership in multidisciplinary teams.
Design and build proactive, human-centred agentic systems that reason, plan, and act across domains like biotech, robotics, and AI. Develop full-stack architectures from edge reasoning to cloud deployment, integrating multimodal sensing and persistent memory. Work in agile, cross-disciplinary teams to rapidly prototype and productionise breakthrough systems for high-impact clients.
This role involves owning critical parts of Anthropic's production pretraining pipeline for large language models, focusing on performance optimization, debugging across hardware and training dynamics, and ensuring reliable, scalable model training. The position requires deep technical expertise in distributed systems and ML frameworks, with hands-on responsibilities during high-pressure model launches and a strong emphasis on operational reliability and cross-team coordination.
This role focuses on ensuring the reliability and resilience of large language model serving systems across the full stack, from API layers to accelerators. You'll design service level objectives, build observability systems, lead incident response, and collaborate across teams to strengthen critical infrastructure. The position demands a systems thinker with strong distributed systems experience and a proactive approach to improving robustness in high-scale AI environments.
Lead the development and application of learning science in AI-powered education solutions, ensuring systems are pedagogically sound, evidence-based, and safe. Define best practices, design evaluations, and mentor cross-functional teams working on national infrastructure, tutoring, and assessment platforms. Translate cognitive science into technical requirements for scalable, data-rich learning systems.
