Python Engineer

O tym stanowisku

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. Engineers have real ownership of technical decisions and a direct impact on system performance and product capabilities.

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.

ABOUT THE ROLE:

We are looking for a Python Engineer with 3–5 years of hands-on experience building Python projects.

Your focus will be on designing and developing structured Python pipelines used for data processing, analysis, experimentation and visualization.

This is not a role for someone who has mainly used Python for isolated scripts. We are looking for an engineer who knows how to take a growing collection of experiments and processing logic and turn it into a clean, maintainable Python codebase with reusable utilities, libraries, classes and well-defined pipelines.

You'll work closely with engineers and researchers working on signal processing, radar and AI/ML, helping them process, explore and understand complex datasets efficiently.

WHAT YOU'LL DO:

- 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 to communicate results and support engineering decisions.

- 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 comfortably in an engineering workflow using Git for version control, Jira for task and sprint management, and Slack for day-to-day 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.

WHAT WE'RE LOOKING FOR:

- 3–5 years of professional experience working with Python, ideally on engineering, scientific, data-intensive or R&D projects.

- Strong practical Python skills — you should be comfortable building complete projects rather than only writing standalone scripts.

- Strong understanding of how to structure a Python codebase 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, extending and working with classes.

- Experience working with numerical or analytical data using libraries such as NumPy, Pandas and/or SciPy.

- Strong EDA skills — ability to investigate datasets, identify patterns, anomalies and data-quality issues, and communicate findings.

- Experience creating technical visualizations with matplotlib, Plotly or similar tools.

- Strong working knowledge of Git, including branches, pull requests, merge workflows and collaborative code review.

- Hands-on experience with Docker, including building and running containers and using containerized development environments.

- Comfortable working with Jira for task tracking, sprint planning and engineering workflows.

- Comfortable using Slack as a primary collaboration and communication tool within an engineering team.

- Ability to write clear, readable and maintainable production-quality Python code.

- Comfortable working in an environment where requirements evolve through experimentation and engineering discovery.

- Strong problem-solving skills and the ability to work independently while collaborating with engineers from different technical disciplines.

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 tools such as pytest.

- Experience with performance optimisation or vectorised numerical processing.

- Previous experience in deep-tech, robotics, autonomous systems, radar, signal processing or another R&D-heavy environment.

WHAT WE OFFER:

- Impact
Build the Python infrastructure that engineers and researchers use to process, analyse and understand real-world data. Your work directly improves how quickly the team can experiment, validate ideas and move technology forward.

- Engineering Challenges Worth Solving
Work with complex datasets and technical problems where clean software engineering has a…