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Mandatory Internship – Product Development Engineer (m/f/d)

ecopals

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placeBerlin home_workOn-site labelProduct Design publicAggregated job · DE

eventPublished on Oct 26, 2026 · verifiedWe confirmed on Oct 26, 2026 that it's still live

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About the job

About ecopals

ecopals is building the leading performance additive platform for asphalt and bitumen modification, engineered for regional, sovereign supply chains and backed by strong unit economics. Our current product line is built on high-performance polymers, with further additive categories in active development. In the last two years, we have scaled to active operations in more than 10 EU countries, while continuously expanding our product and technology platform. As we enter our next growth phase, we are opening a mandatory internship position for Product Development Engineer (m/f/d) .

The role

works closely with our R&D team on the identification, assessment and development of new products, formulations and production routes.

The role

combines materials science and engineering with data analysis and modern AI-assisted technical workflows, with a strong emphasis on using these tools to accelerate development without compromising scientific rigor. Tasks In this internship, you will help turn early technical ideas into structured development programmes and support the evaluation of which product and process routes are worth pursuing. Areas of responsibility Product development research. Researching potential development routes for new products, formulations and processes based on scientific literature, technical documentation, experimental results and first-principles understanding. Development-route assessment. Comparing materials, technologies, mechanisms and production concepts and identifying promising routes for further development. Technical and economic feasibility. Preparing structured assessments and reports on technical feasibility, process requirements, raw materials, costs and potential economic viability. Test programme development. Supporting the design of experimental programmes, including formulation matrices, variables, testing methods and evaluation criteria. Experimental and laboratory support. Preparing material samples for internal testing, external laboratories and customers; assisting with the preparation and execution of in-house experimental setups; and supporting the documentation and evaluation of experimental results. Laboratory coordination. Supporting the planning and coordination of testing activities with internal and external laboratories, suppliers and technical partners. Data analysis. Processing and evaluating experimental data to identify trends, correlations, performance drivers and development priorities. Technical data management. Building and maintaining structured databases for formulations, raw materials, test results, literature and development projects. Programming, data analysis and AI-assisted workflows. Using Python and modern AI-assisted development tools, including AI agents, to clean, structure, analyse and visualize technical data; automate repetitive R&D tasks; support technical research; and build internal analytical workflows. A key part of the role is learning to use these tools effectively and responsibly, with proper validation, documentation and control of the resulting work. Technical standards and regulations. Researching and analysing standards, specifications and regulatory requirements relevant to products under development and their potential applications. Technical reporting. Preparing clear technical reports and decision documents that translate scientific, experimental and economic information into actionable development recommendations. Independent development work. Taking ownership of defined development questions and following them from initial research through analysis and experimental validation.

Requirements

Currently completing a Master’s degree or comparable advanced university programme in Chemistry, Chemical Engineering, Materials Science, Materials Engineering, Process Engineering, Environmental Engineering, Civil Engineering or a related field. Good foundations in chemistry, materials science, construction materials and/or industrial processes . At least two years of relevant experience in one or more of the activities described above , gained through internships, research projects, student assistant positions, laboratory work, industrial projects or professional experience. Strong analytical skills and confidence working with quantitative technical and experimental data. Programming and data-analysis skills , preferably with Python or comparable tools. Previous experience with AI-assisted coding or AI agents is valuable but not required. More important is the ability and willingness to rapidly adopt these workflows and use them rigorously — understanding what the tools are doing, checking their outputs, identifying errors and ensuring that analyses remain technically sound and reproducible. Ability to work systematically with scientific literature, experimental results and complex technical information. Ability to move between fundamental scientific questions and practical engineering and production constraints. A structured and independent way of working, with a strong sense of ownership. Strong written and verbal communication skills in English; German is a plus. An entrepreneurial and pragmatic mindset, with genuine interest in developing technologies that can move from research into industrial application. Your Benefits Direct involvement in product development , contributing to technologies that may become future ecopals products. Exposure to the full development process , from scientific principles and formulation concepts to processes, testing and economic assessment. Practical experimental experience , supporting material preparation, in-house experiments and laboratory validation activities. Hands-on experience with technical data and analytical tools , including opportunities to improve how R&D data is structured, analysed and used for decision making. Practical experience with AI-assisted R&D workflows , including programming, automation and diligent use of AI agents as technical working tool

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