The Senior Machine Learning Engineer will lead the deployment of ML models, design scalable systems, mentor team members, and collaborate with customers to solve engineering challenges.

The Senior Simulation Data Engineer will manage the end-to-end data pipeline for simulation, ensuring high-quality outputs for ML training and collaborating with research teams to optimize processes.

The Senior ML Infrastructure Engineer will manage and optimize the ML infrastructure, focusing on training pipelines, model serving, and collaboration with research teams.

Develop and deploy AI agents for engineering workflows, collaborating with domain experts, and improving the platform's functionality through systematic evaluations.

As a Principal AI Engineer, you'll architect the Agentic stack for AI-driven simulation software, focusing on agent observability, deployment, sandboxing, evaluations, and governance within engineering workflows.

The Senior AI Engineer will build and scale the Agentic platform, implementing AI workflows for engineering, ensuring secure operations and high-code quality.

The Deployment Lead will manage end-to-end deployments of our platform in customer environments, ensuring successful adoption and addressing deployment challenges.

As a Senior Software Engineer, you'll design and operate Kubernetes Operators, manage the runtime layer, and ensure platform reliability and extensibility while mentoring other engineers.

You will enhance the platform's operational health by refining monitoring systems, driving cost efficiency, improving developer experience, and ensuring secure and efficient infrastructure management.

The role involves designing, provisioning, and operating core infrastructure across multiple cloud providers, ensuring its reliability and scalability. Key responsibilities include managing Kubernetes clusters, implementing multi-tenancy, and collaborating on security and compliance initiatives.

The Senior Software Engineer will develop AI-driven simulation software by collaborating with clients, writing clean code, leading projects, and designing systems for engineering applications.

Manage end-to-end recruitment for technical roles (Data Science, Software, ML, Simulation): source candidates, conduct phone screens, coordinate interviews, maintain ATS, support employer branding, and ensure a positive, data-driven candidate experience.

The Senior Product Designer will lead user-centered design for enterprise applications, conducting user research, creating prototypes, collaborating with cross-functional teams, and influencing design practices across the organization.

Lead design and delivery of cloud-native Data Integration Services: define scalable data access patterns, storage integrations, dataset lifecycle and permissioning, ensure observability and governance, and mentor engineers to drive platform adoption.

Design and build scalable microservices, APIs, and data pipelines for high-dimensional simulation data. Implement data storage and ingestion for ML workloads, enable BI and visualization tools, own features end-to-end, maintain CI/CD and observability, and collaborate with data scientists to ensure secure, reliable, performant systems.

Lead design and delivery of cloud-native Data Integration Services to enable discovery, access, sharing, and governance of large simulation and ML datasets. Define data access patterns, storage integrations, permissioning, lifecycle, observability, and platform standards while mentoring engineers and driving cross-team adoption.

Work with customers and cross-functional teams to turn AI-driven simulation research into reusable engineering applications. Build and maintain frontend interfaces and backend services, design APIs, write clean, tested code, optimise performance, and contribute to architecture and CI/CD. Translate customer workflows into product capabilities and mentor junior engineers.