Calibration Algorithms Engineer / Data Analysis Engineer (m/f/d)

We are looking for a Calibration Algorithms Engineer / Data Analysis Engineer to develop, validate, and optimize numerical and statistical algorithms for advanced imaging, calibration, and optical measurement systems.

In this role, you will transform complex measurement and calibration challenges into robust mathematical and computational solutions. You will develop data analysis pipelines, statistical algorithms, simulation models, and automated validation tools while working with empirical data generated across optical measurement systems. Your work will directly support calibration accuracy, measurement quality, algorithm validation, and efficient analysis at scale.

You will work closely with physicists, optical engineers, hardware engineers, and software engineers in a collaborative, cross-disciplinary environment. If you are analytical, hands-on, self-directed, and enjoy solving complex problems using mathematics, data, and software, this role is for you.

Key Responsibilities

• Formulate imaging, calibration, and measurement problems as mathematical models based on physical sensor and light-source characteristics.
• Propose and implement measurement schemes and efficient algorithmic solutions optimized for specific use cases and requirements.
• Develop and evaluate statistical models, numerical algorithms, and figures of merit for optical metrology and measurement data.
• Design, implement, and maintain robust, scalable, and efficient data analysis and visualization software in Python.
• Develop simulation models and contribute to simulations of advanced imaging and metrology systems.
• Build scalable analysis tools and automated batch workflows for high-performance computing (HPC) environments.
• Develop automated verification and validation tools for calibration algorithms and laboratory measurement instruments.
• Analyze, characterize, and summarize empirical data generated across optical measurement systems.
• Benchmark and optimize numerical algorithms for accuracy, stability, performance, and scalability.
• Validate algorithms against simulated models and experimental measurement data.
• Support automated workflows for detecting calibration drift, regressions, and measurement inconsistencies.
• Clearly communicate mathematical reasoning, algorithmic approaches, assumptions, advantages, and limitations to technical stakeholders across disciplines.
• Document algorithms, analysis pipelines, validation methods, and technical workflows to ensure maintainability and effective knowledge transfer.
• Contribute throughout the development cycle, including problem formulation, algorithm design, implementation, validation, optimization, and deployment.

Required Qualifications

• Advanced degree or equivalent experience in applied mathematics, physics, engineering, computer science, or a closely related quantitative field.
• Strong theoretical and experimental background in data analysis, statistics, numerical methods, and visualization.
• Extensive experience developing statistical algorithms, statistical models, or machine learning solutions.
• Strong programming experience in Python for numerical and scientific computing.
• Hands-on experience with NumPy, SciPy, Matplotlib, and related scientific Python tools.
• Strong understanding of numerical linear algebra, including least squares, SVD/eigendecomposition, conditioning, numerical stability, and sparse or large-scale systems.
• Experience developing, characterizing, and optimizing numerical algorithms for accuracy and performance.
• Experience building data analysis pipelines and automated workflows.
• Strong problem-solving skills with the ability to break complex mathematical and technical problems into manageable tasks.
• Ability to work independently, take ownership of technical problems, and quickly learn new physical and engineering domains.
• Excellent written and verbal communication skills in English.
• Ability to collaborate effectively across hardware, software, optical engineering, physics, and other technical disciplines.

Preferred Qualifications

• Strong understanding of object-oriented programming and software design principles.
• Knowledge of Bayesian probability and estimation theory, including likelihood formulation, error propagation, uncertainty quantification, and outlier handling.
• Experience with GPU-accelerated computing frameworks such as CUDA, PyTorch, or MLX.
• Experience with automatic differentiation and modern optimization or solver frameworks such as Ceres, JAX, or CasADi.
• Experience developing algorithms for computational imaging, computer vision, signal processing, or related fields.
• Experience deploying and optimizing software for high-performance computing systems and cluster environments.
• Familiarity with ray tracing, camera models, rendering tools, or optical simulation.
• Understanding of imaging systems, CMOS image sensors, optics, and optical measurement systems.
• Familiarity with optical metrology concepts and measurement system design.

Technical Skills

• Programming: Python, object-oriented programming, scientific computing.
• Data Analysis: NumPy, SciPy, Matplotlib, statistical modeling, data visualization.
• Numerical Methods: Least squares, SVD/eigendecomposition, numerical conditioning, stability analysis, sparse and large-scale systems.
• Algorithms: Statistical algorithms, machine learning, numerical optimization, estimation, uncertainty quantification.
• Validation: Automated testing, algorithm verification, regression detection, calibration drift analysis.
• HPC: Scalable data processing, batch workflows, cluster-based computation, performance optimization.
• Imaging & Optics: Computational imaging, computer vision, camera models, ray tracing, CMOS image sensors, optical metrology.

contract: B2B - Remote

Job Types: Full-time, Temporary, Contract

Work Location: Remote