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# Senior Research Machine Learning Engineer

- **Company:** PhysicsX Ltd
- **Location:** London, United Kingdom
- **Experience:** Expert
- **Salary:** £46,650
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Computer Vision, Microsoft Azure, Big Data, C++ (Programming Language), Computational Fluid Dynamics, Nvidia CUDA, Continuous Integration, Distributed Systems, Job Scheduling, Python (Programming Language), Machine Learning, Tensorflow, Scientific Computating, Software Engineering, Management of Software Versions, Graphics Processing Unit (GPU), Google Cloud, Pytorch, Gpu Programming, Build Management, Machine Learning Operations, Api Design
- **Published:** November 10, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5960207000

## About the Role

* Enthusiasm about using machine learning for science and engineering, and especially in scaling such solutions to real-world settings
 * Ability to work autonomously in a fast-paced environment, learn and adapt quickly, scope, plan and deliver effectively
 * Strong collaboration and communication skills, especially with research scientists
 * Experience with software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps)
 * Experience building ML models and pipelines in Python, using common libraries and frameworks (e.g., PyTorch, TensorFlow, JAX)
 * Experience with the GPU programming ecosystem, ability to optimise models on all levels of the stack, going down to the level of CUDA/Triton/Warp kernels when necessary
 * Experience training and serving ML models at scale
 * Experience with large-scale data processing

 * Domain knowledge in physics and/or numerical methods, especially CFD
 * Experience working in the domain of ML for science or engineering
 * Experience building infrastructure on cloud platforms (e.g., AWS, Azure, GCP, CoreWeave)
 * Experience with C/C++, especially for computer vision, geometry processing and scientific computing

## Description

* Work closely with our simulation engineers and research scientists to develop an understanding of the physics and engineering challenges we are solving
 * Work at the intersection of data science and software engineering to transform prototype implementations to robust production-grade model implementations, libraries and tooling
 * Work with multi-GPU/multi-node distributed systems for training and inference at the scale of PBs of data and hundreds of GPUs
 * Optimize the models and pipelines on all levels, from job scheduling down to GPU kernels
 * Design and build scalable and robust infrastructure for end-to-end machine learning applications on cloud (CoreWeave, AWS)
 * Continuously apply and improve engineering best practices and standards, coach your colleagues in their adoption.