Machine Learning Software Engineer, Research
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Key skills for this role
Role Overview
The role combines machine learning, data science, software engineering, and numerical simulation for science and engineering applications.
The company is recruiting for multiple positions across different levels and asks candidates to apply for the role best aligned with their skills and goals.
Key Skills for This Role
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About PhysicsX
PhysicsX is a deep-tech company building an AI-driven simulation software stack for engineering and manufacturing.
Its customers span aerospace and defense, materials, energy, semiconductors, and automotive industries.
Role overview
The role combines machine learning, data science, software engineering, and numerical simulation for science and engineering applications.
The company is recruiting for multiple positions across different levels and asks candidates to apply for the role best aligned with their skills and goals.
What you will do
- Build and deliver models with research scientists and simulation engineers for real-world physics and engineering problems.
- Design and optimize scalable machine learning models and convert prototypes into robust implementations.
- Implement distributed multi-node and multi-GPU training and explore federated learning with cloud and on-premises services.
- Build and scale foundation models for science and engineering and identify suitable libraries, frameworks, and tools.
- Own research workstreams, communicate results to colleagues and customers, and translate research into reusable products.
- Mentor colleagues with less machine learning or engineering experience.
What you bring
- MSc or PhD in a relevant field such as computer science, machine learning, statistics, mathematics, physics, engineering, or software engineering.
- Experience in scientific computing, CPU or GPU high-performance computing, or parallelized or distributed training for large or foundation models.
- Ability to work autonomously, scope projects, solve problems quickly, and deliver across varied domains.
- Excellent collaboration and communication skills with teams and customers.
Preferred experience
- More than two years of professional experience in a data-driven role is ideal.
- Preferred exposure includes scalable ML and foundation models, distributed and high-performance computing, cloud platforms, Python ML frameworks, C/C++, MLOps, containers, orchestration, and experiment pipelines.
- Federated learning experience is a bonus.
Workplace
- The hybrid model combines time in the Shoreditch office with work-from-home days.
What we offer
- Employees receive equity options, a 10 percent employer pension contribution, free office lunches, enhanced parental leave, and a nursery scheme.
- Additional benefits include 25 days of annual leave plus public holidays, private medical insurance, Wellhub, eye tests, personal development support, and an Employee Assistance Programme.
- The company also offers Bike2Work, a season ticket loan, and an electric vehicle salary-sacrifice scheme.
About physicsx
AI software for physics simulation and engineering optimization.
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