3 months ago
London, United KingdomMid Level
H1B Sponsor
Responsibilities
- Work with research scientists and simulation engineers to build and deliver models for real-world physics and engineering problems.
- Design, build, optimize, and scale machine learning models for application-domain use cases.
- Transform prototype model implementations into robust and optimized implementations.
- Implement distributed training architectures for multi-node and multi-GPU training and explore federated learning across cloud and on-premise services.
- Help design, build, and scale foundation models for science and engineering and optimize training over large datasets and multi-GPU cloud compute.
- Select libraries, frameworks, and tools for modeling efforts.
- Own research workstreams according to seniority.
- Discuss research results and implications with colleagues and customers and connect them to real-world problems.
- Translate research results into reusable libraries, tooling, and products at the intersection of data science and software engineering.
- Mentor and support colleagues with less experience in machine learning and engineering.
Requirements
- MSc or PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, software engineering, or a related field.
- Record of experience in scientific computing, high-performance computing, or parallelized/distributed training for large or foundation models.
- Ideally more than 2 years of professional experience in a data-driven role.
- Experience scaling and optimizing ML models and training or serving foundation models at scale; federated learning experience is a bonus.
- Experience with distributed computing and high-performance computing frameworks such as Spark, Dask, MPI, OpenMP, CUDA, and Triton.
- Experience with cloud computing on hyperscaler platforms such as AWS, Azure, or GCP.
- Experience building machine learning models and pipelines in Python with libraries and frameworks such as NumPy, SciPy, Pandas, PyTorch, and JAX.
- Experience with C/C++ for computer vision, geometry processing, or scientific computing.
- Understanding of software engineering concepts and best practices, including versioning, testing, CI/CD, API design, and MLOps.
- Experience with containerization and orchestration using Docker, Kubernetes, or Slurm.
- Ability to work autonomously, scope and deliver projects across domains, analyze problems, collaborate effectively, and communicate results to colleagues and customers.
- Enthusiasm for machine learning solutions, especially deep learning or probabilistic methods, and supporting software for science and engineering.
Benefits
- Hybrid work model with time in the Shoreditch office and 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.
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.