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- Aufgaben: Support AI/ML Engineers in designing and evaluating speech recognition models.
- Arbeitgeber: Join a cutting-edge company shaping the future of automotive technology.
- Mitarbeitervorteile: Gain hands-on experience while studying, with flexible hours to fit your schedule.
- Warum dieser Job: Be part of innovative projects that enhance in-car experiences globally.
- Gewünschte Qualifikationen: Must be a Bachelor or Master student in Computer Science or related fields.
- Andere Informationen: Ideal for those passionate about machine learning and audio processing.
APCT1_DE
Working Student – Machine Learning (Audio) (f/m/d) Arbeitgeber: Cinemo GmbH
Kontaktperson:
Cinemo GmbH HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Working Student – Machine Learning (Audio) (f/m/d)
✨Tip Number 1
Make sure to familiarize yourself with the latest advancements in Automatic Speech Recognition (ASR) and Text-To-Speech (TTS) technologies. This will not only help you understand the field better but also show your genuine interest during any discussions.
✨Tip Number 2
Engage with online communities or forums related to machine learning and audio processing. Networking with professionals in these spaces can provide valuable insights and potentially lead to referrals.
✨Tip Number 3
Consider working on personal projects that involve training machine learning models for audio data. Having practical examples to discuss can set you apart from other candidates.
✨Tip Number 4
Stay updated on the latest tools and libraries in Python, C/C++, Pytorch, TensorFlow, and Keras. Being able to demonstrate your proficiency in these technologies will be crucial during interviews.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Working Student – Machine Learning (Audio) (f/m/d)
Tipps für deine Bewerbung 🫡
Understand the Role: Make sure you fully understand the responsibilities and requirements of the Working Student – Machine Learning (Audio) position. Highlight your relevant experience in Speech Recognition, Audio Data Processing, and Machine Learning in your application.
Tailor Your CV: Customize your CV to emphasize your academic background in Computer Science or Data Science, as well as any hands-on experience with ASR/TTS technologies. Include specific projects or coursework that demonstrate your skills in Python, C/C++, and machine learning frameworks like Pytorch and TensorFlow.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for machine learning and audio technologies. Mention any relevant projects or experiences that align with the job description, and express your enthusiasm for contributing to the next-generation automotive infotainment middleware.
Proofread and Submit: Before submitting your application, carefully proofread all documents to ensure there are no errors. Make sure your application is complete and accurately reflects your qualifications. Submit your application through our website to ensure it reaches the right team.
Wie du dich auf ein Vorstellungsgespräch bei Cinemo GmbH vorbereitest
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, C/C++, and machine learning frameworks like Pytorch and TensorFlow. Bring examples of projects you've worked on, especially those related to Speech Recognition or Audio Data Processing.
✨Understand the Role of ASR/TTS
Familiarize yourself with Automatic Speech Recognition and Text-To-Speech technologies. Be ready to explain how these systems work and their applications in automotive infotainment, as this will demonstrate your genuine interest in the field.
✨Prepare for Practical Scenarios
Think about real-world user scenarios you could create and test for improving in-car experiences. This shows your ability to apply theoretical knowledge to practical situations, which is crucial for this role.
✨Ask Insightful Questions
Prepare thoughtful questions about the team's current projects, challenges they face, and future developments in audio machine learning. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.
