ADAS ML Engineer Position

Description:

Automotive is the first major industry that our client is disrupting by building on our foundational leadership differentiation and scale in mobile. In just a few years our client has gone from newcomer to trusted technology leader in the automotive infotainment segment securing design wins with many of the major automakers worldwide. Automakers have come to rely on us not only for modem technology where our client is the #1 semiconductor in telematics but also as their trusted partner for redefining the incar infotainment and autonomous driving experience. We have established our thirdgeneration infotainment product line and are now a leader in the automotive infotainment category for nextgeneration designs. Snapdragon is expanding in its capabilities to power the next generation cockpit experience as driving assistance and the media and information centre in the vehicle. Which drives significant audio video graphics camera and generic software complexity. Topics like hypervisors AI/ML or SIL/HIL testing are daily topics for us.

This position is for our client’s Automotive Engineering team which closely collaborates with its automotive partners and customers from concept to commercialization. The team involves with all aspects of embedded software such as SW & HW designs feature prototyping feature development integration customization performance optimizations & improvement and other debugging efforts which is key for a successful launch of the product.

We are looking for a strong software engineer (m/w/d) with good knowledge and handson experience in design/development/debugging aspects of board support packages (BSP) and the generic software platform. The position is part of a regional expert team which has the responsibility to provide consultation to our client’s customers and partners to accomplish their design and development goals. Topics like debugging our client’s SW related issues and help to customize/optimize software using the features in our client’s SOC play a major role in the daily work. The candidate must quickly rampup onto existing projects understand automotive platform hardware and software driver architecture demonstrate strong analytical and systematic problemsolving abilities and is happy to work with external customers to customize and launch their new products.

The successful candidate will get a chance to work on cutting edge infotainment/digital cockpit and ADAS technologies from leading auto manufacturers and Tier1s and contribute to push the projects through to commercialization.

Required Profile:

Strong Software Applications Engineering Software Development experience or related work experience.

– Good development or debugging experience with High level operating systems (QNX Linux or Android)

Generic but solid understanding the machine learning/deep learning concepts algorithms and architectures including CNNs used for Object Detection Segmentation and various other Computer Vision tasks.

Background and understanding of neural network operators and mathematical operations like linear algebra or quantisation issues.

Experience with executing analysing and optimising neural networks (e.g. pruning quantization etc. especially for embedded systems applications. Knowledge of frameworks and SDKs for Computer Vision/Deep Learning like OpenCV OpenCL PyTorch Tensorflow Caffe/Caffe2.

Excellent issue triage and debugging skills with complex system level issues.

An intrinsic desire for systematic working and ability to deliver high quality results in a stressful environment.

Good communication and excellent team working skills.

Quick adaptability to work in new technologies.

Ability to take up project management responsibilities and basic understanding of software development processes.

Driving license for Germany and ability to freely travel within Europe and North America.

Ability to lead a small crossfunctional team and mentoring junior team members in technical and nontechnical topics.

Technical Qualifications:

Experience with Automotive Infotainment or ADAS projects.

Experience with performance optimisation and debugging of data pipelines for image processing.

Practical experience with ML applications in Automotive Infotainment or Autonomous Driving projects.

Experience with industry standard ML benchmark suites such as ML Perf.

Experience with ML accelerators or other dedicated hardware blocks for ML in embedded systems.

Practical experience with the optimisation of neural networks for embedded applications.

Education:

Bachelor's degree in Engineering Information Systems Computer Science Electronics or related field (Masters Preferred)