Senior Scientific Software Engineer — Simulation and Machine Learning

Role overview

This senior engineering position focuses on building the simulation and model-learning engine at the core of a quantum software platform. The work sits at the intersection of physics and engineering, combining differentiable simulation of physical systems with machine-learning-driven parameter inference and large-scale numerical optimisation. It is a research-grade engineering role with a clear delivery mandate rather than a pure research post or a general software position.

Responsibilities

- Build and maintain high-performance simulation code for open and closed quantum systems - Own the differentiable simulation and automatic differentiation layer, and drive performance inside optimisation loops - Implement parameter inference and model learning from experimental data - Develop neural-network approaches to PDE solving and equation discovery - Benchmark against established academic tools and publish the comparisons - Collaborate with faculty on joint research and grant proposals, supervise graduate students and interns, and contribute to teaching material on numerical simulation and ML for physics

Requirements

- PhD or equivalent in physics, applied mathematics, or computational science - Strong scientific computing background in Julia, Python, JAX, or comparable environments - Genuine numerical depth in ODE solvers, optimisation, stochastic processes, and automatic differentiation - Published research or widely used code that others rely on - Ability to take a method from a paper and turn it into fast, tested, usable software - Clear technical writing and fluent English

Nice to have

- Interest in supervising students alongside engineering work - Comfort owning code quality, not just correctness - Motivation to contribute to teaching and curriculum development

Benefits and work setup

- Remote within Europe with regular on-site presence in Bremen - Hybrid working model combining remote flexibility with time on-site - Route into teaching and student supervision for those who want it - Direct involvement in core technical work with measurable impact on performance and accuracy