Your mission You will - work on machine learning research projects, in particular addressing the question of how machine learning methodolog
Entwickelt KI-Systeme, die Vision und Sprache für die Autonomie schwerer Robotermaschinen verbinden, und begleitet sie bis zum Produktiveinsatz.
Master s degree or PhD in Computer Science, Information Systems, Robotics, Computer Vision, or a related field.
When travelers are searching for a hotel, we want the obvious choice to be trivago!
SpAItial is pioneering the next generation of World Models, pushing the boundaries of generative AI, computer vision, and the simulation of reality.
Wir schreiben dir, sobald eine neue geprüfte Stelle dazukommt. Höchstens eine Nachricht am Tag, und nur, wenn es tatsächlich etwas Neues gibt.
Abmelden mit einem Klick, jederzeit. Keine Weitergabe an Dritte.
define and own the data science and AI strategy across the organization - lead development and scaling of predictive and generative AI model
SpAItial is pioneering the next generation of World Models, pushing the boundaries of generative AI, computer vision, and the simulation of reality.
SpAItial is pioneering the next generation of World Models, pushing the boundaries of generative AI, computer vision, and simulation.
As an AI/ML Engineer, you will play a crucial role in designing, developing, and optimizing machine learning models to power our mobile applications.
Your mission Join our ranking team and build the intelligent systems at the core of Cosuno s platform.
Bridge the gap: Develop and maintain the hardware abstraction layers that allow our higher-level autonomy modules to interact seamlessly with the physical robot.
Taktile empowers financial institutions to transform into truly AI-native organizations.
As an AI/ML Engineer, you will play a crucial role in designing, developing, and optimizing machine learning models to power our mobile applications.
We are seeking an experienced Machine Learning Engineer (MLE) to focus on audio model evaluation, specifically for speech generation and recognition models.
We’re looking for a Research / ML Engineer to join our Speech Team to build state-of-the-art speech systems end-to-end—from data specs throu
is hands-on and code-heavy — you will work inside the same monorepo as the research team, mostly in Python, and should be as comfortable ref
Lead R&D efforts to prototype a new robotic manipulator, conducting rigorous testing to validate design specifications and performance criteria.
Entwickelt theoretische Rahmenwerke und Architekturen für sichere KI-Systeme und beweist probabilistische Sicherheitsgarantien unter Daten- und Rechenbeschränkungen.
adjoe builds the technologies behind mobile apps growth and monetization.
At ARX Robotics, you will help advance the perception capabilities of next-generation unmanned ground vehicles.
Own ML and GenAI systems end-to-end in production, including problem framing, system design, deployment, monitoring, and continuous improvem
Overview We are looking for experienced Machine Learning and AI Experts to help train and evaluate advanced AI models.
We are seeking a Machine Learning (ML) Manager to join our growing team dedicated to a novel AI safety agenda.
As a Software Engineer, you will build the world leading Agentic AI product for biomedical researchers by combining robust engineering pract
Warum dieser Job gelistet ist
Eindeutige KI-Rollenbezeichnung im Stellentitel. Prüfverfahren ansehen
You have - a MSc or PhD in mathematics, physic, computer science or a related field - published academic papers; machine learning related papers are a plus - a creative mind that likes to solve problems - grounded knowledge about machine learning and deep learning in particular Why us? You will work with an interdisciplinary team of people with a solid background in mathematics and statistics. We offer flexible working hours (full and part time) and have a nice office with good coffee in Berlin Kreuzberg, close to Moritzplatz.
We prefer a hybrid work model, but are open to remote work. We believe in science and support with publishing your research results. Here are short descriptions of some projects we have worked on.
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 modeling), and detecting different paragraphs automatically, before tackling the inference task.
Your mission You will - work on machine learning research projects, in particular addressing the question of how machine learning methodologies can be further improved in order to achieve better performances in relevant applications; those applications are likely to be connected to either computer vision or natural language processing, however, also more general methodological questions might be of interest (e.g. meta learning, hyperparameter search, efficient training of neural networks) - also work on transferring theoretical insights to practical use cases which are usually part of respective research projects, with the goal of setting new industry standards - be able to publish your results in relevant journals or at machine learning conferences such as ICML, NeurIPS or ICLR - foster our strong connections to academia, keep up to date with advances in machine learning research and actively take part in our company’s collaborative learning and development environment - support the dida team in applying cutting-edge machine learning algorithms
Interesse an dieser Position?
Die vollständige Anzeige und das Bewerbungsformular liegen beim Arbeitgeber.
Zur OriginalanzeigeModelle bauen, trainieren und verbessern: von klassischem Machine Learning über Computer Vision bis zum Feinschliff großer Sprachmodelle.