Working Student
vor 1 Tag
**Jobnummer**: 49311
**Gruppe**:Magna Electronics
**Division**:Magna Electronics Sailauf
**Art der Beschäftigung**:Befristete Anstellung
**Standort**:Sailauf
**Group Description**
Magna Electronics Europe GmbH & Co. OHG is heavily engaged in end-to-end solution development for ADAS/AD systems and aiming to be lead tier-1 world-wide.
- Functional performance validation of the ADAS/AD systems is a major contributor to evaluate and qualify the developed technology / functionalities / products and assure compliance with regulations’ bodies like NCAP (global, EU, Japan), NHTSA and release them on public road (during development phase) and in series production (for OMEs)._
**Job Summary**:
- Ground truth generation is one of the key aspects in perf. validation of ADAS / AD functions, demands state of the art technology, involve high amount of manpower and significant cost._
- Currently, lot of ground truth generation/annotation is happening manually, consuming lot of time and money. In recent years AI, machine learning (ML) and deep learning (DL) becoming a big technology revolution driver (inc. ADAS/AD)._
- This student work is a master thesis extension of technical feasibility study, design, development (as proof of concept) and aiming to generate targeted ground truth/annotation automatically (for smaller-larger datasets) using AI, ML and DL. Also, one wants to analyze cost benefits, quality and limitation of the solution._
**Duties and Responsibilities**:
- Review the existing master thesis work with us
- Extend the ML and DL models to full-fill larger data-based auto annotation capabilities
- Further develop relevant tooling and deploy in AWS for day-to-day use
- Also support engineering team in further developing data analytics tests (functional Perf. Testing in ongoing projects)
**Requirements and Qualifications**:
- Master Student of computer engg., automotive embedded engineering, or similar
- Programming Skills:
- Python, Numpy, Pandas, Matplotlib
- Github (Version Control)
- PyTorch
- Working know-how of Machine Learning and deep learning
- Working know-how of Convolutional Neural Networks
- Lidar points based based Object Detection (The problem you will be working on is object detection. So, please get a good understanding of object detection using Convolutional Neural Networks)
- Comprehensive knowledge of English (speak & write)
**Benefits**:
- Collegial, supportive and friendly working atmosphere with a "Duz" culture
- Attractive and performance-oriented compensation package
- Prospects and opportunities for personal and professional development through various training offers
- Individual work arrangements through flexible working hours and opportunities to use "Office Work" and "Mobile Work" personally
- Corporate benefits program
- International and diverse environment and open door culture
**_ We have aroused your interest, then convince us with a personal cover letter and your complete documents, indicating a possible start date and salary expectations, on our career homepage_
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