Jobs at PhysicsX

As a DevOps Consultant at PhysicsX, you will manage customer deployments, design strategies, troubleshoot issues, and ensure platform success in various environments.

As a Forward Deployed Software Engineer, you will develop applications leveraging physics AI models, collaborating with data scientists and customers, and design E2E solutions while deploying APIs and microservices.

Lead data science workstreams to build production-ready deep learning and probabilistic models integrated with multi-physics simulations. Own data preprocessing, scalable data pipelines, model architecture, deployment, cross-functional collaboration, customer-facing co-development, internal R&D, and mentoring of junior team members.

Lead development and deployment of deep learning and probabilistic models for multi-physics engineering problems. Architect scalable data pipelines, collaborate with simulation engineers, drive R&D, mentor junior team members, and work directly with customers to integrate models into production, including onsite customer collaboration and presentations.

The Senior Machine Learning Engineer will lead the deployment of ML models, mentor engineers, and influence product decisions, while collaborating directly with customers on-site to solve engineering challenges across various industries.

The Senior CFD Engineer will build complex multi-physics models, work with clients on engineering challenges, and deliver high-fidelity simulations, while mentoring junior colleagues and integrating AI tools.

The Principal Machine Learning Engineer will lead efforts in deploying ML models, architecting data systems, mentoring teams, and driving project scoping with a strong focus on customer collaboration.

The Senior FEA Engineer will create advanced simulation models, automate FEA tools, partner with customers to solve engineering challenges, and mentor junior staff, while traveling up to 2-3 weeks quarterly.

As a Senior Forward Deployed Software Engineer, you will build and deploy applications utilizing AI-driven physical models to optimize engineering processes for clients across diverse industries.

Collaborate with research scientists and customers to design, train, and productionise physical foundation models. Scale multi-GPU training, convert prototypes into robust implementations, choose tooling and frameworks, own research workstreams, and translate research into reusable libraries, tooling and products while mentoring colleagues.

Conduct research and build ML models (neural operators, geometric deep learning, generative models) to predict physical system behavior; own research streams, collaborate with engineers and customers, run experiments, publish results, and mentor peers.