5 beste Stellen als machine learning python in zürich, zh – aktuell auf Personalsuche

Generalist Engineering Intern - Drones & Applied AI
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- Englisch
- C++
- Erfahrung in der IT
2 Std.
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Generalist Engineering Intern - Drones & Applied AI
Wingtra AG —Zürich, ZH
A strong overlap with a few of them, plus high agency and strong learning ability, is more important. The team explores new technologies, prototypes product…
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Generalist Engineering Intern - Drones & Applied AI

Wingtra AG
Zürich, ZH

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Details zur Stelle

Praktikum
vor 2 Stunden

Qualifikationen

Git
Englisch
C++
Erfahrung in der IT
Linux
Python

Vollständige Stellenbeschreibung

Join the Wingtra team and become part of this venture-backed robotics scaleup with a global and international team of 125+ dedicated Wingtranauts who want to see their actions have a positive and lasting impact on the world. Founded more than 8 years ago at ETH Zurich, Europe’s leading robotics university, our goal is to build the best aerial robots to digitize the world at the push of a button and set the basis for faster and better decisions. Wingtra provides efficient and reliable data solutions to a variety of industries ranging from mining, construction and agriculture to humanitarian organizations, environmentalists and wildlife monitoring groups.

We are reaching for the stars and together we might just get there. Open communication, asking hard questions and valuing diverse viewpoints are but a few things that will help us achieve our goals. Above all we will never stop learning and striving to help each other reach our maximum potential.

During your internship at Wingtra, you will be fully onboarded into a small, highly cross-functional team working closely with the CTO. The team explores new technologies, prototypes product ideas, and turns early technical concepts into working systems that can be tested on real drones, real hardware, and real customer-relevant workflows. See our Search and Rescue solution WingtraSAR.ai as one of the many projects we work on.

This broad engineering role is for those who enjoy end-to-end building. Projects may involve firmware, drone hardware, electronics, mechanical prototyping, web tools, computer vision, machine learning, data analysis, or cloud applications. You do not need expertise in all areas; we prioritize curiosity, agency, engineering taste, and a proven ability to solve problems through building.

The starting date is ASAP if possible (or up to September 2026), and the duration will be 6 months or longer.

Responsibilities

As a generalist engineering intern, you will work with and assist highly driven and experienced engineers to achieve ambitious goals. You may contribute across several of the following areas, depending on your strengths and the project needs:

Prototype and test systems integrating software, electronics, mechanics, and drone hardware.
Develop firmware and embedded software for microcontrollers and peripherals.
Handle hardware tasks including soldering, wiring, debugging, and assembling test rigs.
Design mechanical parts and enclosures using CAD and rapid prototyping tools.
Build internal tools and full-stack applications using Python, TypeScript, or React.
Evaluate CV/ML approaches for automation, mapping, and drone-related data processing.
Contribute maintainable code to existing codebases and adapt open-source components.

Requirements

We are looking for someone who is highly curious, self-driven, and comfortable working across disciplines.

You should be able to show that you have a:

Proven track record of building substantial projects independently (hobby, professional, or open-source).
Self-directed learner comfortable with technical ambiguity and complex debugging.
Strong engineering judgment focused on reliability over simple demos.
Proficiency in spoken and written English.
Degree (in progress or completed) in Robotics, CS, Engineering, or equivalent practical experience.

The strongest candidates will have concrete examples of things they have personally built. We are especially interested in projects that went beyond coursework and involved solving real-world problems, your own or for others, and showed some sustained iteration on it.

Plus

You do not need experience in all of the areas below. A strong overlap with a few of them, plus high agency and strong learning ability, is more important.

Relevant experience could include:

Firmware / embedded: C/C++, microcontrollers, protocols (CAN, UART, I2C, SPI), and embedded Linux.
Robotics: PX4, ROS/ROS 2, autopilots, MAVLink, GNSS, and simulation.
Hardware: Hands-on electronics, soldering, debugging, and test rig assembly.
Mechanical: CAD design for mounts/enclosures and rapid prototyping (3D printing, CNC).
Software: Python, C++, TypeScript, Git, and maintainable Linux development.
Web: Full-stack tools using React, Node.js, and cloud APIs.
CV/ML: PyTorch, OpenCV, object detection, and edge deployment.
Data: Log analysis, automation scripts, and large dataset processing.

What we care about most

We value independent builders who are creative, who love to learn, dig into complex systems and develop amazing new capabilities into them, and watch their creations go out into the real world and make a difference! Ideal candidates have independently developed technically serious projects - such as drones, robots, web tools, or CV/ML pipelines - driven by a genuine interest in making them work!

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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Erweiterte Suche

machine learning python Jobs in zürich, zh

Generalist Engineering Intern - Drones & Applied AI

Engineer III, AI/ML, Online Calibration, XR

DevOps Engineer /Deployment Manager

Data Architect mit einem Flair für AI

Wissenschaftliche/-r Mitarbeiter/-in für Fernerkundung und Machine Learning zur Modellierung trockenheitsbedingter Waldschäden

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