About Us
PhysicsX is a deep‑tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI‑driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high‑fidelity, multi‑physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.
Who We’re Looking For
As a Data Scientist in Delivery, you are a problem solver and builder who is passionate about creating practical solutions that enable customers to make better engineering decisions. You are someone who can grasp advanced engineering concepts across multiple industries, and you excel at working directly with customers (and often side‑by‑side with them on‑site) to transform cutting‑edge AI models into tools that are useful and used.
You’ve worked on difficult problems that require strong foundations in data‑driven modelling and deep learning techniques, with hands‑on experience in probabilistic methods and predictive modelling. Expertise in Python, along with proficiency in libraries like NumPy, SciPy, Pandas, TensorFlow and PyTorch, is essential, with the ability to deploy scalable, production‑ready models and data pipelines.
With at least 1 year industry experience (post‑Masters or PhD) in a commercial, non‑research environment, you’re ready to hit the ground running. You’re truly excited about growing your technical expertise and are naturally inclined to take ownership of data science work streams, continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers.
This Role
In this role, you’ll work closely with our Simulation Engineers, Machine Learning Engineers, and customers to understand and define the engineering and physics challenges we are solving.
You’ll build the foundations for successful, impactful solutions by:
- Pre‑processing and analysing data to prepare it for use in predictive modelling, building the foundation for machine learning algorithms to be developed.
- Developing and utilising innovative deep learning models in combination with state‑of‑the‑art optimisation methods to predict and control the behaviour of physical systems.
- Taking full responsibility for the quality, accuracy and impact of your work.
- Designing, building and testing data pipelines that are reliable, scalable and easily deployable in production environments.
- Working closely with simulation engineers to ensure seamless integration of data science models with simulations.
- Contributing to internal R&D and product development, helping to refine models and identify new areas of application.
- Engaging in open communication and presentation with both technical teams and customers, helping onboard users and co‑develop with customers.
- Traveling to customer sites in North America, Europe, Asia and Oceania an average of 2‑3 weeks per quarter, collaborating closely with customers to build solutions onsite.
This role is based in London, working 2‑3 days per week in our central office.
What We Offer
- Equity options – share in our success and growth.
- 10% employer pension contribution – invest in your future.
- Free office lunches – great food to fuel your workdays.
- Flexible working – balance your work and life in a way that works for you.
- Hybrid set‑up – enjoy our new Shoreditch office while keeping remote flexibility.
- Enhanced parental leave – support for life’s biggest milestones.
- Private healthcare – comprehensive coverage.
- Personal development – access learning and training to help you grow.
- Work from anywhere – extend your remote set‑up to enjoy the sun or reconnect with loved ones.
We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.
We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.
