physicsx · London, United Kingdom
Skills: Python, AWS, CI/CD
About us Re-architecting Engineering for the Age of Intelligence PhysicsX is the physics AI company for industrials. The company’s mission is to accelerate hardware innovation by overhauling what industrial engineering and manufacturing look like today. PhysicsX is building a new simulation software stack to deliver deep physics AI enablement across the entire engineering lifecycle. The company partners with leading organisations in aerospace & defence, automotive, semiconductors, materials, and energy & renewables, supporting them on some of their most critical and complex challenges. PhysicsX is headquartered in the United Kingdom, with offices in London, New York, and Singapore and an expanding presence in the Bay Area. What you'll do 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. What you'll bring 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…
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