As a software engineer, you’ll develop and conceptualize highly innovative software solutions using the C / C++ programming languages for autonomous driving and connected services
Real-time and hardware-related programming would be your focus
You’ll work in an agile and well-distributed team and would be involved in the whole process of system and software development
Which means you’ll contribute to the software development process starting from design till implementation and test
Constant exposure to the latest technologies and methods of software development are guaranteed and you’ll be the professional contact person for your colleagues and our customers
We offer you an attractive salary and a competitive overall package
Regular and systematic (external and internal) further training opportunities
Modern style of working in an innovative and international team
University degree in computer science, electrical engineering or a comparable field
Experience in low-level programming of ECUs with C / C++ and MQTT or IoT services from AWS or Microsoft is desirable
You have expertise in AUTOSAR or RTOS and are familiar with CAN, LIN or Ethernet on ECU level
You have the passion to gain first experiences with development tools such as Jira, DOORS codeBeamer or Enterprise Architect
Experience in software development processes such as SCRUM or V Model and ASPICE.
Very good verbal and written communication skills in English as well as the ability to work in a team
Shaping the next Level of Autonomous Things
AUTONOMOUS REPLY is a company within the Reply Group specializing in software and system integration of autonomous things.
Our experts advise companies in the industrial, automotive and new mobility sectors on everything - from sensor to infrastructure.
Our portfolio includes holistic solutions covering the entire value chain - from strategy definition and consultancy on possible applications up to design and implementation.
Our solutions include edge computing, embedded software, cloud services and integration into various eco systems, utilizing state-of-the-art technologies and methods from the fields of deep learning, machine learning and computer vision.