Mathematical Algorithm Engineer – m/f/d

Capgemini

. Develop mathematical models, calibration algorithms, and numerical solution methods for complex optical measurement and inspection systems .

Posted 11/4/2026contractRemote • GermanyMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and validating mathematical models and algorithms, particularly in C++ and Python, while ensuring accuracy and robustness in numerical solutions. Proficient in analyzing measurement data and conducting sensitivity analyses, with strong capabilities in both German and English communication.

Highest-signal resume keywords

Mathematical ModelingC++ ProgrammingPython ProgrammingNumerical Optimization MethodsStatistical Estimation Theory

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Mathematical AlgorithmsNumerical Linear AlgebraBayesian ModelingSensitivity AnalysisUncertainty AnalysisOptimization ProblemsInverse ProblemsSignal ProcessingComputational ImagingNumerical Simulations

Tools & Technologies

NumPySciPy

Industry Keywords

Optical MeasurementInspection SystemsLaboratory EnvironmentsTechnical SpecificationsDevelopment Documentation

Tech Stack

Tools & technologies

NumpyPythonTypeScriptC++

About the role

Key responsibilities & impact

Develop mathematical models, calibration algorithms, and numerical solution methods for complex optical measurement and inspection systems
Formulate and solve optimization, estimation, and inverse problems while taking accuracy, stability, and numerical robustness into account
Implement, test, and optimize algorithms in C++ and Python
Ensure performance, convergence, and quality requirements are met
Analyze measurement data and conduct sensitivity and uncertainty analyses
Validate simulation results against real experimental data from laboratory environments
Document mathematical models, solution approaches, and results in technical specifications, white papers, and development documentation

Requirements

What you’ll need

Completed degree in mathematics, physics, computer science, computational science, electrical engineering, or a comparable field
Relevant professional experience in developing, implementing, and validating mathematical algorithms in a scientific or industrial environment
Excellent knowledge of numerical linear algebra
Excellent knowledge of numerical optimization methods
Excellent knowledge of statistical estimation theory
Excellent knowledge of Bayesian modeling
Excellent skills in developing and implementing mathematical algorithms with C++ and Python
Knowledge of NumPy and SciPy is an advantage
Experience with numerical simulations, inverse problems, signal processing, or computational imaging is an advantage
Fluent written and spoken German and English

Benefits

Comp & perks

Specialized training
Mentoring
Innovative projects
Location-flexible work depending on project requirements and team coordination
Flexible working hours
Work across multiple locations
Work in a diverse and open team
Broad range of learning opportunities for professional and personal development
Temporary assignment to a customer project