Python Engineer

Our client is a European deep-tech startup developing next-generation radar systems for the detection and tracking of small, low-flying drones. The team works across radar architecture, RF hardware, signal processing, embedded systems, AI and data-processing software. This is a hands-on R&D environment for engineers who enjoy working with complex technical data, building reliable software tooling, and turning experimental workflows into structured, reusable systems.

• 3–5 years of professional experience working with Python, ideally on engineering, scientific, data-intensive or R&D projects.
• Strong applied Python skills, comfortable building complete projects rather than isolated scripts.
• Experience structuring Python codebases using modules, packages, utilities and reusable libraries.
• Ability to design and develop multi-step data-processing pipelines with clear inputs, transformations and outputs.
• Strong understanding of object-oriented programming in Python and confidence creating and extending classes.
• Experience working with numerical or analytical data using NumPy, Pandas and/or SciPy.
• Strong exploratory data analysis (EDA) skills.
• Experience creating technical visualizations with matplotlib, Plotly or similar tools.
• Strong working knowledge of Git, including branches, pull requests, and code review.
• Hands-on experience with Docker, including building and running containers.
• Comfortable using Jira for task tracking and sprint planning.
• Comfortable using Slack for team communication.
• Ability to write clear, readable and maintainable production-quality Python code.
• Ability to work independently and collaboratively in an evolving experimental environment.

Nice to have:

• Experience working on Data Science or Machine Learning projects.
• Familiarity with scikit-learn, PyTorch or similar ML libraries.
• Experience processing large numerical, sensor, time-series or signal datasets.
• Experience supporting researchers or ML engineers by turning notebooks and prototypes into reusable software.
• Familiarity with testing Python applications using pytest.
• Experience with performance optimisation or vectorised numerical processing.
• Previous experience in deep-tech, robotics, autonomous systems, radar, signal processing or other R&D-heavy environments.

• Build Python pipelines — Design, implement and maintain modular pipelines for loading, processing, transforming, analysing and exporting technical data.
• Structure Python projects — Turn experimental scripts and notebooks into maintainable packages with clear modules, utilities, libraries and interfaces.
• Develop reusable components — Build internal utilities and libraries that can be reused across experiments, datasets and engineering workflows.
• Object-oriented development — Design and work confidently with Python classes, inheritance/composition where appropriate, interfaces and reusable abstractions.
• Data analysis & EDA — Explore datasets, identify patterns and anomalies, validate assumptions and help engineers understand what is happening in the data.
• Data visualization — Build clear technical visualizations using tools such as matplotlib, Plotly or similar libraries.
• Work with scientific Python — Use libraries such as NumPy, Pandas and SciPy to process and analyse numerical and time-series data.
• Improve engineering quality — Refactor existing code, reduce duplication, introduce clear abstractions and help establish good practices around maintainability, testing and documentation.
• Containerize development workflows — Use Docker to create reproducible development and execution environments.
• Collaborate effectively — Work in an engineering workflow using Git for version control, Jira for task and sprint management, and Slack for team communication.
• Work with R&D teams — Collaborate closely with signal-processing, radar and AI/ML engineers to translate experimental requirements into reliable Python tooling and pipelines.

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