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.
Note: We are currently recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals.
What you will do- Work closely with our simulation engineers, data scientists and customers to develop an understanding of the physics and engineering challenges we are solving
- Design, build and test data pipelines for machine learning that are reliable, scalable and easily deployable
- Explore and manipulate 3D point cloud & mesh data
- Own the delivery of technical workstreams, potentially while mentoring more junior colleagues
- Create analytics environments and resources in the cloud or on premise, spanning data engineering and science
- Identify the best libraries, frameworks and tools for a given task, make product design decisions to set us up for success
- Work at the intersection of data science and software engineering to translate the results of our R&D and projects into re-usable libraries, tooling and products
- Continuously apply and improve engineering best practices and standards and coach your colleagues in their adoption
What you bring to the table- Enthusiasm about using machine learning for science and engineering
- Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly
- Excellent collaboration and communication skills - with teams and customers alike
- (For more experienced candidates) Passion and track record of managing, mentoring and coaching more junior colleagues
- 3-6 years’ experience in a data-driven role, with exposure to software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps)
- Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., TensorFlow, MLFlow)
- Distributed computing frameworks (e.g., Spark, Dask)
- Cloud platforms (e.g., AWS, Azure, GCP) and HP computing
- Containerization and orchestration (Docker, Kubernetes)
- Ability to scope and effectively deliver projects
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 setup – 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 setup 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.
Apply for this jobTo apply, please submit your information as requested in the application form. Fields include name, email, resume/CV, and other standard details as indicated in the form.
