Senior ML Engineer for Physics Simulations at Scale

PhysicsX; City Of London; Hybride; GBP 70 000 - 120 000; Plein temps

Avantages offerts par ce poste

Equity options

25 days annual leave

Private medical insurance

Pension contribution

Wellbeing benefits

Parental leave

Cycle to work

Résumé du poste

PhysicsX is seeking engineers to work with simulation scientists to turn prototype ML into robust production models and tooling. You will scale training across multi-GPU systems and optimize pipelines, from scheduling to GPU kernels, while building cloud-based ML applications.

We value collaboration, autonomy, and a passion for applying ML to science and engineering, with strong software practices and cloud experience. Hybrid UK-based role.

Qualifications

• Interest in applying ML to scientific and engineering challenges.
• Ability to work autonomously in a fast-paced environment with rapid learning.
• Strong collaboration and communication with researchers.
• Experience building ML models and pipelines in Python using PyTorch, TensorFlow or JAX.
• Familiar with GPU programming and scalable ML workflows.

Responsabilités

• Collaborate with simulation engineers and researchers to understand ML challenges.
• Transform prototype implementations into production-grade models, libraries and tooling.
• Work with multi-GPU/multi-node distributed systems for training and inference at large scale.
• Optimize models and pipelines from scheduling to GPU kernels.
• Design infrastructure for end-to-end ML applications on cloud platforms (CoreWeave, AWS).
• Promote engineering best practices and mentor colleagues.

Connaissances

ML for science

Autonomous work

Collaboration

Software engineering basics

Python ML (PyTorch, TF, JAX)

GPU programming

ML models at scale

Big data processing

Formation

Outils

PyTorch

TensorFlow

JAX

CUDA

Triton

Warp

MLOps

CI/CD

Description du poste

PhysicsX is seeking engineers to work with simulation scientists to turn prototype ML into robust production models and tooling. You will scale training across multi-GPU systems and optimize pipelines, from scheduling to GPU kernels, while building cloud-based ML applications.

We value collaboration, autonomy, and a passion for applying ML to science and engineering, with strong software practices and cloud experience. Hybrid UK-based role.