Senior AI Researcher

This is not a traditional research role.

This is where cutting-edge AI research meets real-world engineering problems that actually matter.

There is already a working system.

There are real users pushing its limits.

There are hard constraints from physics, performance, and scale.

What’s missing is a researcher who can take bold ideas and turn them into systems that work in production.

We are building AI-driven models that replace traditional physics simulations with high-speed, accurate alternatives. These systems are being applied to complex engineering challenges across advanced industries, where accuracy, speed, and reliability are critical.

The Opportunity

This is a foundational research role with real ownership.

You will not be publishing in isolation or experimenting without constraint. You will define research directions and ensure they translate into production systems that deliver measurable impact.

You will operate at the intersection of deep learning, physics, and high-performance systems.

If you enjoy solving problems that do not have established solutions, this is that kind of environment.

What You Will Work On

• Designing novel ML architectures for complex physical systems and simulation problems

• Applying approaches such as Transformers, graph-based models, or generative methods to scientific domains

• Solving challenging problems around representing geometry and physical constraints in ML models

• Bridging the gap between research and production, ensuring models are performant and deployable

• Collaborating closely with engineers and domain experts to integrate models into real-world workflows

This is hands-on research. You will be writing code, building models, and seeing them used in practice.

What Success Looks Like

First few months:

• You take ownership of key research problems and begin shaping technical direction

• Early ideas translate into working prototypes tested on real-world data

• You establish credibility across both research and engineering teams

First year:

• You define core parts of the research roadmap

• Your models are deployed and delivering measurable improvements

• You help establish the company as a serious player in applied AI research

What We’re Looking For

You are a researcher who:

• Has a strong academic background in machine learning, physics, mathematics, or a related field

• Has taken models from research into real-world or production environments

• Is highly proficient in frameworks such as PyTorch, TensorFlow, or JAX

• Understands optimisation, generalisation, and model architecture at a deep level

• Thinks beyond papers and cares about performance, scalability, and real-world impact

• Thrives in fast-moving, ambiguous environments with high ownership

Nice to Have

• Experience with physics-informed machine learning or scientific AI

• Familiarity with areas like fluid dynamics, simulations, or engineering systems

• Background in distributed training or high-performance compute

• Publications in leading ML or AI conferences

Why Join

• Full ownership: shape the research direction and see it applied in practice

• High impact: your work directly enables real-world engineering breakthroughs

• Elite team: work alongside people solving genuinely hard technical problems

If this sounds interesting, apply or reach out to learn more.