Working Student Machine Learning (m/f/d)
Updated: 16 Dec 2024
Über das Unternehmen
Cinemo is a highly innovative one-stop-shop provider for fully integrated digital media products. They are ready for every screen, combining high performance, high quality, low footprint, and cutting-edge technologies in a truly system-agnostic design.
Whether embedded, as mobile apps or through the cloud, Cinemo offers digital media products any industry.
As a Working Student – Machine Learning (Audio) you will support the Senior AI/ML Engineers in the design and evaluation of Automatic Speech Recognition (ASR) / Text-To-Speech (TTS) machine learning models.
What do we offer?
- Office spaces in the heart of the city center
- A friendly, diverse, international, dynamic, challenging and open-minded work environment
- Flexible working hours
- The opportunity to shape the future of infotainment
- Talent management initiatives
- Great social events throughout the year
- Working partly remote is possible
In this role, you will:
- Support our Senior AI/ML Engineers in the design, training and evaluation of ASR/TTS/Audio ML models and underlying software architecture
- Collect, analyze, prepare and structure datasets for training, validation and testing state-of-the-art machine learning models and technologies to be used in the next-generation automotive infotainment middleware
- Create and test real-world user scenarios to elevate the future in-car experience across different car-lines worldwide
What you will need to succeed:
- Active study program as Bachelor or Master student in the field of Computer Science, Data Science or equivalent
- First hands-on experience with Speech Recognition, Speech Synthesis and Audio Data Processing
- od kledge in Machine Learning, Deep Learning, Transformer and Large Language Models
- Practical experience in training/fine-tuning, validation and evaluation of ML models
- Proficiency in Python, C/C++, Pytorch, TensorFlow, Keras
Unser Jobangebot Working Student Machine Learning (m/f/d)klingt vielversprechend?Bei unserem Partner Workwise ist eine Bewerbung für diesen Job in nur wenigen Minuten und ohne Anschreiben möglich. Anschließend kann der Status der Bewerbung live verfolgt werden. Wir freuen wir uns auf eine Bewerbung über Workwise.
10 - 20 hours per week hours per week