Senior Scientific Software Engineer — Simulation and Machine Learning

Posted Yesterday
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Hiring Remotely in Germany
Remote
Senior level
Information Technology
The Role
Build and maintain high-performance differentiable simulation software for open and closed quantum systems using Julia and Python. Develop model-learning, parameter-inference, neural-network PDE-solving, and optimisation methods. Benchmark research methods, improve performance and reliability, collaborate with university faculty, publish results, supervise students and interns, and contribute to teaching materials.
Summary Generated by Built In

Location: Remote within Europe, with regular presence in Bremen

Direct Reports: None; supervision of students and interns

Working Model: Remote / hybrid. Regular time on-site in Bremen.

Mission

Build the simulation and model-learning engine at the centre of Constructor's quantum software. The work is numerics-heavy: differentiable simulation of physical systems, inference of model parameters from experimental data, and optimisation at scale. The role sits between physics and engineering and requires genuine depth in both.

Responsibilities

Pillar 1 Simulation Engine

  • Build and maintain high-performance simulation code for open and closed quantum systems.
  • Own the differentiable simulation and automatic differentiation layer.
  • Drive performance. This code runs inside optimisation loops and speed decides what is possible.
  • Maintain and extend the Julia core and its Python interface.

Success Metrics and KPIs: simulation accuracy against measurement, runtime performance, API stability.

Pillar 2 Model Learning and Optimisation

  • Implement parameter inference and model learning from experimental data.
  • Work on neural-network approaches to PDE solving and equation discovery.
  • Benchmark against established academic tools and publish the comparison.

Success Metrics and KPIs: benchmark results, methods adopted by the research group, publications.

Pillar 3 Research Collaboration

  • Work with Constructor University faculty on joint research and grant applications.
  • Supervise graduate students and interns working on the engine.
  • Contribute to course material on numerical simulation and machine learning for physics.

Accountability: research collaborations initiated and sustained; students productive.

Requirements

Experience

  • PhD or equivalent in physics, applied mathematics or computational science.
  • Strong scientific computing in Julia, Python, JAX or comparable.
  • Real numerical depth: ODE solvers, optimisation, stochastic processes, automatic differentiation.
  • Published work, or code that others rely on.

Skills & Competencies

  • Able to take a method from a paper and make it fast, tested and usable.
  • Comfortable owning code quality, not only correctness.
  • Interest in supervising students alongside the engineering.
  • Clear technical writing.

Education & Languages

  • PhD in physics, applied mathematics or computational science.
  • Fluent English.
What This Role Is (and Is Not)

This role IS

  • A research-grade engineering role with a product at the end of it.
  • Central to the group's core technical asset.
  • A role with a route into teaching and supervision if you want it.

This role is NOT

  • A pure research position without delivery.
  • A general software engineering role.
  • A role where someone else owns the numerics.

Skills Required

  • PhD or equivalent in physics, applied mathematics, or computational science
  • Strong scientific computing experience in Julia, Python, JAX, or comparable technologies
  • Expertise in numerical methods including ODE solvers, optimisation, stochastic processes, and automatic differentiation
  • Published work or software code relied upon by others
  • Ability to implement methods from research papers as fast, tested, usable software
  • Ability to take ownership of code quality and correctness
  • Interest in supervising students and interns
  • Clear technical writing skills
  • Fluent English
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The Company
Year Founded: 2024

What We Do

Constructor Knowledge Labs (CKL) is a research institute based in Bremen, Germany, dedicated to advancing applied research in Computer Science, Software Engineering, Machine Learning, and Artificial Intelligence across interdisciplinary domains.

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