Software Engineer - Hardware Abstraction for Machine Learning, Engineering Center, Cluj

Company Description

At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people's lives. Whether in areas of Automated Driving, Electric & Connected Mobility, IoT or Connectivity, our ideas make driving safer and more comfortable than ever before. This is only possible with the help of more than 1000 talented engineers from Bosch Engineering Center Cluj specialized in software, hardware & mechanics and reliability engineering, who work closely together with other Engineering Centers within Bosch and with Bosch Cluj Plant in order to offer unique products and AIoT solutions to our clients from around the world. 

So, are you ready to shape the future of the mobility together with us? Let us tell you more. Our promise to our associates is rock-solid: we grow together, we enjoy our work, and we inspire each other. Join in and feel the difference.

• Education: Bachelor or Master's degree in Computer Science, Informatics, Mathematics, Automation and Industrial Informatics, Electronics and Telecommunications or comparable.
• Personality and Working Practice: enthusiastic, self-motivated, persistent and responsible character, keen to share ideas, willing to drive things forward, not afraid to provide open and honest feedback and excited to work in a highly motivated team.
• Experience and Knowledge: You have at least 2 years of computer science and software engineering skills, especially with reference to digital hardware, compiler technology and coding in C++ and Python;
• You have knowledge of machine learning algorithms as well as ML hardware accelerators with multiple years of practical experience in these fields;
• You have experience with hardware-aware neural architecture search and network compression as well as knowledge of automotive System-on-Chips (for example Nvidia, Renesas, TI) is a big plus;
• Proficiency in English is mandatory;
• German know-how is a plus.

Nice to have:

• You are passionate about self-driving vehicles, radar technologies, algorithms, software, data;
• You have an engineering mindset and a strong interest in new technologies;
• You have know-how or willingness to learn more from one of the following fields: pattern recognition, signal processing, computational geometry, statistics, etc;
• You have knowledge of several optimization techniques for at least one embedded platform with the aim of achieving real-time performance;
• You have experience with parallel programming/multi-threading, thread synchronization and scheduling;
• Assembly language programming knowledge is a plus;
• You have GPU programming skills (CUDA, OpenCL);
• You possess low level programming know-how (DSPs, FPGAs);
• You have knowledge of SIMD instructions sets:

1. MMX, SSE, AVX - for x86, x64 based platforms

2. Neon, SVE, Helium - for ARM based platforms

#LikeABosch Benefits:

 Hybrid working is the new way of working! We offer super nice and cozy office spaces, however you can also work from home if you feel like it (70% remote work) 

Our #LikeABosch benefits:  

• 25 days of annual leave 
• Medical subscription 
• Accident insurance 
• A monthly budget which can be used for several different services on an online benefit platform 
• Annual bonus 
• Relocation bonus
• Lunch discounts  
• Sport activities and well-being initiatives 
• Technical and soft skills trainings 
• Access to e-learning platforms 
• Local and Global career development programs 
• Bookster subscription 

We are currently looking for a Software Engineer for Hardware Abstraction Layer for Machine Learning to work within our team which improves life by innovating autonomous driving/riding systems.

Within the Automotive business sector, we lay the foundation for radar-based assistance systems functions, such as predictive emergency breaking and adaptive cruise control.

In your role you will:

• Optimize machine learning algorithms for automotive embedded hardware and you harvest the benefits of dedicated ML accelerator hardware;
• Design and implement hardware abstraction layers for machine learning algorithms and a compiler framework for translating AI models to hardware-specific optimized models and code;
• Work with AI developers and hardware experts and develop solutions for our overall build toolchain;
• Collaborate with multiple international teams across the world.

Technology Stack:

• Programming Languages: C/C++;
• Target - CPU: ARM Cortex A family or similar;
• Target - Hardware Accelerators: DSPs, GPUs, Neural Networks Accelerators, etc;
• Versioning system: Git.