Intern Full Stack Engineer Typescript / Python

🌍 Intern Full-Stack Engineer 🌍 🚀 Build the future of sustainable tech with us! 🚀 Location: 🌍 Remote with 4 hours overlap with Amsterdam time Pay: 💶 €800/month for a minimum of 32 hours per week Duration: 🕒 6+ months Who We Are Welcome to Spatialise, where we're blending full-stack engineering, data science, and machine learning magic to tackle real-world problems and make a lasting impact. Backed by a dream team from Wageningen University, ex-IBM leadership, and machine learning innovators from Bain & BCG, we're on a mission to empower organizations to build sustainable systems that truly make a difference. 🌱✨ What You'll Be Doing 💡 Develop end-to-end features: Build modern, responsive interfaces using React and scalable backend systems with Node.js. ⚙️ Engineer robust systems: Design, implement, and optimize APIs, databases, and CI/CD pipelines. 📊 Tackle data challenges: Work on large datasets, implement parallel compute frameworks like Dask, and optimize data flows for performance. 👩‍💻 Learn SRE practices: Dive into building reliable systems, monitoring, and infrastructure-as-code. 🎓 Grow with us: Take part in our mentorship and training programs to level up your TypeScript and Python expertise. Who You Are A final-year Bachelor's or Master's student in Computer Science, Software Engineering, or a related field. Solid full-stack foundation with experience in React, Node.js, APIs, and database systems. Familiarity with CI/CD pipelines and deployment processes. Passionate about data engineering, including experience with Dask or parallel compute frameworks. Skilled in TypeScript and eager to explore Python for data tasks. A startup mindset—proactive, adaptable, and thrives in an environment of rapid iteration and shifting priorities. Interest in growing into Site Reliability Engineering (SRE), focusing on system reliability, scaling, and security. Bonus Points 🌟 Experience with observability tools, monitoring systems, or infrastructure-as-code. 🌟 Confidence in handling large datasets and debugging performance bottlenecks. 🌟 A collaborative spirit—shares knowledge openly, gives and receives feedback constructively, and documents thoroughly.

Welcome to Spatialise, where we're blending full-stack engineering, data science, and machine learning magic to tackle real-world problems and make a lasting impact. Backed by a dream team from Wageningen University, ex-IBM leadership, and machine learning innovators from Bain & BCG, we're on a mission to empower organizations to build sustainable systems that truly make a difference.