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Senior Machine Learning Researcher

Starting Salary of £70k - £100k

Inspired by the environmental challenge, driven by the desire to solve problems long considered too difficult, Monumo is changing the game. At Monumo we are combining human ingenuity with deep tech intelligence to deliver more sustainable designs and solve engineering problems impossible by conventional means.

Our methodology—using human creativity to set parameters but AI to determine the best possible answers—opens the door to optimal solutions and disruptive new design ideas that would be impossible or at the very least improbable without this blend of great engineers and compute power.

Our focus at present is on the engineering design problem of electric motors – a mature but increasingly vital technology with plenty of room for improvement. However, the techniques and the creativity employed to solve the engineering and technical problems of improving motor performance can be applied to other challenges. The tools we are creating can be applied to clean energy generation, aviation, heavy industry, manufacturing, robotics… there’s a lot to optimise.

Every effort must be made to solve the climate crisis, to protect the Earth’s resources, reduce the materials we use, increase the efficiency and performance of things we make and reduce their impact. Monumo can play a meaningful part in this change.

We are a well-funded start-up based in central Cambridge UK. Our core team brings together complimentary skills and expertise from Arm, Microsoft Research, Deepmind, Siemens and Academia. We really value everyone’s individual experience and the different perspectives, skills and humour they bring to our team.

Why we need you:

What we are doing is fundamentally novel. You may come from a physics, computer science or engineering background – we're very open minded about that. We need you to help us solve complex interdisciplinary problems to improve how most of the world’s energy is used by optimising electric motors to their fundamental limits. You will be working on a wide variety of interesting tasks in a multi-disciplinary team of hardware engineers, physicists, machine learning researchers and computer science experts.

What you’ll bring that we will value:

Below are some of the skills and motivations we’re looking for in this role. Don’t worry if you don’t tick all of them! More important is your willingness to grow, be flexible and learn new things.

Knowledge and Skills

  • PhD or equivalent experience in the industry
  • Excellent research and problem-solving skills
  • A proven track record in probabilistic modelling of physical systems and/or Bayesian optimisation
  • 2+ years research on ML applications in the physical world with a focus on surrogate modelling and/or design optimisation
  • 5+ years professional experience with Python and ML-frameworks, such as PyTorch, Tensorflow, or jax
  • Expertise with Bayesian modelling techniques including (Deep) Gaussian processes, Bayesian neural networks, latent variable models, and variational inference
  • A passion for interdisciplinary thinking and ML applications in heterogenous teams
  • Experience with scalable and reproducible design of ML systems

If you have any of these, that would be great

  • Experience with statistical inference frameworks such as Stan, Pyro, or Edward
  • Interest in physics and hardware engineering
  • Distributed programming experience
  • Linux scripting experience

You will thrive in our team if you are motivated by:

  • Solving real world technical problems by being open minded and using interdisciplinary thinking
  • Learning new things and technologies – expanding your mindset and professional growth
  • Sharing ideas about how we can do things better
  • Having autonomy as well as collaborating with team members from different backgrounds (physics, engineering)
  • Working in a dynamic environment
  • Passion for developing a purpose-driven business that will make a difference in people's lives.