Machine Learning Working Student - Hybrid | Jobs at dida Datenschmiede GmbH

Machine Learning Working Student - Hybrid

Working Student, Part-time · Berlin

Your mission

dida is a machine learning software company with exciting problems for instance in computer vision and natural language processing. Our team tackles applied problems for different customers by using latest scientific advancements (especially in deep learning) and therefore believes that research oriented thinking can help solving real-world problems more efficiently. And for this we need a Machine Learning Working Student, who will:

support our interdisciplinary team of people, who have a solid background in mathematics and statistics
work on an interesting machine learning tasks, ranging from research projects to industry products
shape and develop our projects and products, together with our machine learning experts

Your Profile

You are studying mathematics, physics or computer science.
You have very good grades in mathematically-oriented subjects.
You are interested in applied statistics and in programming with Python, Julia or something alike.
You are eager to learn more about modern machine learning approaches such as deep learning.
You are planning to stay in Berlin at least 1.5 more years and to work 15-20h/week.
And you want to solve real-world problems with creative ideas.

Why us?

You get the opportunity to grow professionally with us and quickly assume significant responsibilities.
You will work with and learn from people who believe in knowledge sharing and treat each other very sensitively.
We are in an exciting phase where you can actively contribute to shaping the development of dida. With us, you will have the chance to take on responsibility and make your mark.
You will have flexible, hybrid working hours and a nice office with good coffee in Berlin Schöneberg.

We have maintained our curiosity from day one, which means that we want to learn and explore new things. If you want to learn more about our projects, here you find two examples. You can find more here:

Estimate the amount of solar panels that fit on a roof (computer vision):
Given a satellite picture and a ground image of a house, automatically detect certain elements of a roof (including obstacles, dormers etc.) in order to find out how many solar panels fit on it. This involves inferring 3d information from 2d pictures in order to infer the roof pitch.
Detect, classify and suggest legal effectiveness of text paragraphs (NLP):
Automatically go through thousands of legal documents with the goal to classify dedicated paragraphs and check their legal effectiveness. This involves converting scans to text, coming up with a labelling scheme (problem modelling), and detecting different paragraphs automatically, before tackling the inference task.

Please attach the following documents:

CV (mandatory)
(Uni) Degree(s) (mandatory)
Transcripts (where applicable)
Project / Code Examples / Portfolio (optional) - what helps us, in getting to know you better

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About us

dida is a machine learning software company with exciting problems for instance in computer vision and natural language processing. Our team tackles applied problems for different customers by using latest scientific advancements (especially in deep learning) and therefore believes that research oriented thinking can help solving real-world problems more efficiently.

At dida, we stand for equal opportunities, regardless of gender, nationality, ethnic background or disability. We encourage everyone, especially women, people of color, and people with disabilities to apply at dida.

Warum du dich für uns entscheiden solltest?

Wir haben uns vom ersten Tag an unsere Neugierde bewahrt, das heißt, wir wollen lernen und Neues entdecken. Dabei gehen wir im Team sehr sensibel miteinander um. Wir sind nicht hierarchisch organisiert, sondern arbeiten in Zirkeln zusammen. Wenn Du mehr über unsere Projekte erfahren willst, findest du hier zwei Beispiele.

Schätzung der Anzahl von Sonnenkollektoren, die auf ein Dach passen (Computer Vision):
Anhand eines Satellitenbildes und eines Bodenbildes eines Hauses sollen bestimmte Elemente eines Daches (einschließlich Hindernisse, Dachgauben usw.) automatisch erkannt werden, um herauszufinden, wie viele Sonnenkollektoren darauf passen. Dies beinhaltet die Ableitung von 3D-Informationen aus 2D-Bildern, um die Dachneigung zu ermitteln.

Erkennen, Klassifizieren und Vorschlagen der rechtlichen Wirksamkeit von Textabschnitten (NLP):
Automatisches Durchgehen von Tausenden von Rechtsdokumenten mit dem Ziel, bestimmte Absätze zu klassifizieren und ihre rechtliche Wirksamkeit zu überprüfen. Dies beinhaltet die Konvertierung von Scans in Text, die Entwicklung eines Etikettierungsschemas (Problemmodellierung) und die automatische Erkennung verschiedener Absätze, bevor die Inferenzaufgabe in Angriff genommen wird.

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Über uns

dida ist ein Softwareunternehmen mit dem Schwerpunkt Machine Learning, das sich mit spannenden Problemen zum Beispiel in den Bereichen Computer Vision und Natural Language Processing beschäftigt. Unser Team befasst sich mit angewandten Problemen für verschiedene Kunden, indem es die neuesten wissenschaftlichen Fortschritte (vor allem im Bereich Deep Learning) nutzt und glaubt, dass forschungsorientiertes Denken dabei helfen kann, Probleme in der realen Welt effizienter zu lösen.

dida steht für Chancengleichheit, unabhängig von Geschlecht, Nationalität, ethnischem Hintergrund oder Behinderung. Wir ermutigen alle, insbesondere Frauen, People of Color und Menschen mit Behinderungen, sich bei der dida zu bewerben.

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Your application!

We appreciate your interest in our company. Please fill in the following short form. Should you have any difficulties in uploading your files, please contact us by mail at jobs@dida.do.