Chemical/Process Engineer - Scientific Software

Chemical / Process Engineer Scientific Software

Simreka | Scientific backend application features & modules

About the role

Simreka builds enterprise scientific software for chemicals, materials, and manufacturing (Virtual Experiments, formulation intelligence, process and sustainability workflows).

We are hiring a Chemical / Process Engineer with strong software and computational experience to work across the full stack of scientific product development:

1. Scientific backend models, solvers, data pipelines, validation

2. Application features and modules: product capabilities customers use in production

This is a domain-facing engineering role. You will combine process engineering, chemical engineering, data science, and computational engineering to turn physical science into reliable software, then into shipped product modules.

What you will do

Scientific backend

• Design and implement backend scientific engines: property models, process models, formulation logic, optimisation and simulation workflows

• Encode thermodynamics, transport, kinetics, unit operations, and materials behaviour into robust, tested software components

• Build computational pipelines (numerical methods, solvers, batch/async jobs, experiment orchestration)

• Develop data and feature pipelines for scientific and industrial datasets (lab, process, literature, customer data)

• Apply data science and statistical methods for validation, uncertainty, surrogate models, and model monitoring

• Define APIs and contracts so product modules can consume scientific services safely and reproducibly

Application features and modules

• Turn backend capabilities into product features and modules inside Simreka applications (e.g. Virtual Experiments, formulation tools, process/sustainability workflows)

• Work with product and design on user-facing scientific workflows: inputs, constraints, results, explainability, audit trails

• Integrate modules with platform services (auth, jobs, storage, deployment patterns for cloud / on-prem/hybrid)

• Improve performance, reliability, and maintainability of modules used in enterprise implementations

• Support customer-facing activities: workshops, solution design, validation discussions, and implementation feedback loops

Cross-cutting

• Collaborate with Scientific AI, Platform, Engineering, and Delivery

• Document assumptions, limits, and validation status for enterprise trust

• Contribute to reusable methods, accelerators, and internal standards

• Mentor others at the boundary of engineering science and software

Domain mix we expect

Chemical engineering: Reaction systems, separations, phase behaviour, property estimation

Process engineering: Flowsheets, unit operations, operating constraints, scale-up thinking

Computational engineering: Numerical methods, simulation, optimisation, high-quality scientific code

Data science: Data pipelines, statistical validation, surrogates, uncertainty, experiment design support

Product software: Backend services application modules, APIs, testing, delivery with customers

What we look for

Must-have

• Degree in Chemical Engineering, Process Engineering, or related field (MSc preferred; PhD welcome if hands-on)

• Experience building scientific or technical software backends (models, solvers, pipelines not only scripts)

• Experience delivering application features or modules on top of scientific/technical backends

• Strong Python (or equivalent) for scientific computing and service-style code

• Solid grounding in process / chemical engineering fundamentals used in real industrial problems

• Ability to work with data: cleaning, validation, metrics, and honest uncertainty

• Clear communication with both engineers and scientists; comfort in customer-facing technical discussions

• Evidence of ownership: shipped backend + product outcomes, not only analysis

Strong advantages

• Process simulation, digital twins, formulation, materials informatics, or sustainability/process metrics

• ML/AI applied to process or materials problems

• APIs, CI/CD, containerised jobs, enterprise deployment awareness

• Experience in chemicals, specialty materials, polymers, energy materials, or manufacturing R&D

• Prior work in scientific product companies or industrial software