AI · Python
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.
The role
You will own the product capability that lets PhysicsX and its customers improve LLMs for their specific work.
You will be a hands-on product ML engineer embedded deeply with our Research group and accountable for turning post-training methods into something customers can use. The first goal is to make open models perform strongly on the evals and benchmarks that matter to us. The longer-term goal is a repeatable platform capability through which customers can train models on their own workflows keeping their data, learned behaviour and intellectual property under their control.
The remit is broader than supervised fine-tuning. You will choose and apply the right post-training methods, including preference optimisation, reinforcement learning, distillation, synthetic data and verifier-based approaches. You will own the capability roadmap and