Machine Learning Researcher - Python | PyTorch | Machine Learning | Deep Learning | Generative Models
At our organization, we are united by a shared commitment to addressing environmental challenges and finding innovative solutions to complex problems. Together, we are shaping a future where technology meets sustainability, combining human ingenuity with advanced technologies to deliver more sustainable designs and solve engineering problems that are otherwise unattainable by conventional means.
Our methodology opens the door to optimal engineering solutions and groundbreaking new design ideas, made possible by blending exceptional engineering talent with computational power.
Currently, we focus on the engineering design challenges of electric motors—a mature yet increasingly vital technology with substantial room for improvement. However, the techniques and creativity applied to enhancing motor performance are transferable to other sectors, including clean energy generation, aviation, heavy industry, manufacturing, and robotics. There’s a lot to optimize!
We are committed to addressing the climate crisis by protecting resources, reducing materials usage, enhancing efficiency, and minimizing environmental impact. Electric motors account for a significant proportion of global electricity consumption and are crucial for transport decarbonization. Our organization aims to play a meaningful role in driving this change.
We are a well-funded start-up based in a vibrant UK city. Our core team comprises professionals with complementary expertise and experience in cutting-edge technology, research, and academia. We deeply value diverse perspectives, skills, and experiences, as well as the unique contributions each team member brings.
Why We Need You
Your role will involve tackling complex interdisciplinary challenges as part of the ML/AI team. You’ll use data from numerical simulations to generate innovative new motor designs, employing techniques such as deep learning, genetic algorithms, model-based optimization, and generative AI. You’ll work on diverse tasks alongside a multidisciplinary team of hardware engineers, physicists, machine learning researchers, and computer science experts.
We are looking for an experienced AI practitioner who wants to apply their expertise to design optimization challenges for real-world engineering devices, starting with electric motors and extending to physics-driven systems.
What You’ll Bring
We are open-minded about your academic or professional background, whether in physics, computer science, or engineering. Below are the skills and motivations we seek. Don’t worry if you don’t meet all of them—your willingness to grow and learn is more important.
Knowledge and Skills
* PhD or equivalent experience in industry
* Excellent research and problem-solving skills
* 2+ years of experience applying ML to physical systems, focusing on surrogate modeling and/or design optimization
* 5+ years of professional experience with Python and ML frameworks (e.g., PyTorch)
* Background in AI for Science, such as protein design, climate modeling, computational fluid dynamics, or material science
* Expertise in generative approaches, including diffusion models or geometric deep learning
* Interest in interdisciplinary thinking and collaboration
* Experience with scalable, reproducible ML system design
Nice-to-Have Skills
* Experience or interest in PDE modeling with neural networks
* Interest in physics and hardware engineering
* Experience with reinforcement learning
* Distributed programming and cloud computing experience
* Linux proficiency
What Motivates You
You’ll thrive if you’re passionate about:
* Solving real-world technical problems through open-minded, interdisciplinary thinking
* Expanding your knowledge and professional growth
* Sharing ideas and improving processes
* Balancing autonomy with collaboration in a dynamic team
* Contributing to a mission-driven organization making a tangible difference
Rewards and Benefits
* Competitive salary based on experience (£70k–£120k)
* Generous holiday allowance, including time off over the holiday season
* Paid sabbatical every five years for personal growth or rejuvenation
* Comprehensive parental leave policies
* Mental and physical well-being support
* Benefits including healthcare, life assurance, pension contributions, and more
* Equity options for all employees
* Flexible working arrangements with a minimum of three office days per week
* Support for ongoing training and development
* Referral bonuses for successful hires
Machine Learning Researcher - Python | PyTorch | Machine Learning | Deep Learning | Generative Models