2 months ago
Responsibilities
- Collaborate with research scientists, simulation engineers, customers, and partners to deliver AI models for physics and engineering problems.
- Design and build physical foundation models and efficiently scale training across large datasets and multi-GPU cloud compute.
- Transform research prototypes into robust, optimized implementations and challenge architecture decisions that limit scalability.
- Select and advocate for effective libraries, frameworks, and tools.
- Own research workstreams according to seniority.
- Communicate results and implications to colleagues and customers, including their real-world applications.
- Translate research outcomes into reusable libraries, tooling, and products at the intersection of data science and software engineering.
- Foster curiosity and initiative among colleagues and mentees.
Requirements
- MSc or PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, software engineering, or a related field.
- A record of experience in scientific computing, high-performance computing using CPU/GPU clusters, or parallelized/distributed training for large or foundation models.
- Enthusiasm for machine-learning solutions, especially deep learning or probabilistic methods, and supporting software for science and engineering.
- Ability to work autonomously, scope projects, and deliver across varied domains.
- Strong problem-solving, analytical, collaboration, and communication skills.
- Ideally more than 2 years of professional experience in a data-driven setting.
- Preferred exposure to scaling and optimizing machine-learning models, training and serving foundation models at scale, federated learning, distributed and high-performance computing frameworks, cloud computing, Python machine-learning pipelines, deep learning, C/C++, containerization, orchestration, and systematic experiment pipelines.
Benefits
- Hybrid work model combining time in the Shoreditch office with work-from-home days.
- Equity options.
- 10% employer pension contribution.
- Free office lunches.
- Enhanced parental leave, including 3 months full-pay paternity leave and 6 months full-pay maternity leave.
- YellowNest nursery scheme.
- 25 days of annual leave plus public holidays.
- Private medical insurance with 100% employee cover.
- Wellhub subscription.
- Eye tests.
- Personal development support.
- Employee Assistance Programme.
- Bike2Work scheme and season ticket loan.
- Octopus EV salary sacrifice scheme.
Tech Stack
Categories
AI ResearchML Engineering
About PhysicsX
PhysicsX is a physical AI company on a mission to accelerate innovation and overhaul what engineering and manufacturing look like today. We are building a new software stack to deliver deep AI enablement across the entire engineering lifecycle. PhysicsX partners with leading organizations in aerospace & defense, automotive, semiconductors, materials, and energy, supporting them on some of their most critical and complex challenges. PhysicsX is headquartered in the United Kingdom, with offices in London and New York. We are currently recruiting for multiple positions, however, please only apply for the role that best aligns with your skillset and career goals.