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About the Role
PhysicsX is an AI-driven simulation software company focused on accelerating hardware innovation. We are building a simulation software stack for engineering and manufacturing across advanced industries, enabling high-fidelity, multi-physics simulation through AI inference to unlock new levels of optimization and automation.
Responsibilities
- Work closely with research scientists and simulation engineers to build and deliver models addressing real-world physics and engineering problems.
- Design, build, and optimize machine learning models with a focus on scalability and efficiency.
- Transform prototype model implementations into robust and optimized versions.
- Implement distributed training architectures for multi-node/multi-GPU training and explore federated learning capacity using cloud and on-premise services.
- Design, build, and scale foundation models for science and engineering, optimizing model training for large data and multi-GPU cloud compute.
- Identify the best libraries, frameworks, and tools for modeling efforts.
- Own Research work-streams at different levels, depending on seniority.
- Discuss work results and implications with colleagues and customers, focusing on addressing real-world problems.
- Translate research results into reusable libraries, tooling, and products at the intersection of data science and software engineering.
- Foster a nurturing environment and mentor colleagues with less experience in ML/Engineering.
Requirements
- Enthusiasm for developing machine learning solutions, especially deep learning and/or probabilistic methods, and associated supporting software solutions for science and engineering.
- Ability to work autonomously, scope, and effectively deliver projects across various domains.
- Strong problem-solving skills with the ability to analyze issues, identify causes, and recommend solutions quickly.
- Excellent collaboration and communication skills with teams and customers.
- 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.
- Record of experience in high-performance computing (CPU / GPU clusters).
- Record of experience in parallelized / distributed training for large / foundation models.
- Ideally >2 years of experience in a data-driven role in a professional setting.
- Exposure to scaling and optimizing ML models, training and serving foundation models at scale (federated learning a bonus).
- Exposure to distributed computing frameworks (e.g., Spark, Dask) and high-performance computing frameworks (MPI, OpenMP, CUDA, Triton).
- Exposure to cloud computing (on hyper-scaler platforms, e.g., AWS, Azure, GCP).
- Experience building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications.
- Experience with C/C++ for computer vision, geometry processing, or scientific computing.
- Experience with software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps).
- Experience with containerization and orchestration (Docker, Kubernetes, Slurm).
- Experience writing pipelines and experiment environments, including running experiments in pipelines systematically.
Skills
- Deep learning
- Probabilistic methods
- Machine learning
- Distributed training
- Federated learning
- Scientific computing
- High-performance computing
- Distributed computing frameworks
- Cloud computing
- Python
- PyTorch
- JAX
- C/C++
- Software engineering
- Containerization
- Orchestration
Location
- Shoreditch office
Work Type
- Hybrid
Experience Level
- Multiple levels
-
2 years
Education Level
- MSc
- PhD
Benefits
- Equity options
- 10% employer pension contribution
- Free office lunches
- Enhanced parental leave (3 months full pay paternity, 6 months full pay maternity)
- YellowNest nursery scheme
- 25 days of Annual Leave (+ Public Holidays)
- Private medical insurance (100% employee cover)
- Wellhub Subscription
- Eye tests
- Personal development support
- Employee Assistance Programme (EAP)
- Bike2Work scheme
- Season ticket loan
- Octopus EV salary sacrifice
About the Company
- 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.
- Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.
Equal Opportunity
- 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.