Staff SW Engineer Machine Learning - Edge Acceleration (m/f/d)
At CARIAD, we're bundling and further expanding the Volkswagen Group's software expertise. We’re uniting over 6,500 global experts to build a scalable technology stack, including a software platform, unified electronic architecture and reliable connection to the automotive cloud.
Our CARIDIANS are developing vehicle functions such as driver assistance systems, a next-generation infotainment platform, power electronics and charging technology, and digital services in and around the vehicle.
Our software can already be found in Volkswagen ID. models and will soon power Audi and Porsche vehicles with the E3 1.2 platform in 2024.
It's no easy task, but with experts like you, we can shape the future of mobility. Join us at CARIAD and be part of this exciting journey!
YOUR TEAM
BigLoop & Advanced Systems’ is a division of CARIAD SE that holds the E2E responsibility for unifying all activities across domains to accelerate VW Group’s shift towards data driven development (D3).
The overarching goal is to build one holistic data system, which encompasses existing systems across domains as well as brands within VW Group.
We adopt a development practice of DevOps and SRE while constructing the next-gen big-data system of CARIAD SE. Our multi-national team of engineers is leveraging computer vision, big data, simulations, and high-performance computing to design our own software system for CARIAD’s customer features, such as autonomous driving.
We invite you to join us as we tackle complex real-life scenarios and develop tomorrow’s software and hardware solutions of future mobility.
The qualified candidate will perform his / her magic and inject his / her entrepreneurial spirit into a new team by actively contributing to the exploration of unchartered territory and integrating the team into a large-scale organization.
Therefore, this position is best suited for high achievers who love to champion new ideas and challenge the status-quo.
WHAT YOU WILL DO
- Define Edge AI optimized network architecture and deploy end-to-end deep learning solutions for real-time inference in the vehicle
- Conduct in-depth analysis of inference performance and other system variables that impact performance
- Optimize inference and machine learning tasks in C++ and Python
- Implement highly efficient machine learning algorithms on Edge AI embedded hardware
- Work with a growing team of backend engineers, cloud architects, embedded engineers and DevOps experts to develop novel inter-continental (automotive) cloud solutions
- Identify and mitigate project technology risks and execution risks
WHO YOU ARE
- Master of Science in computer science, machine learning, applied mathematics or a similar quantitative area with outstanding grades10+ years of SW / Machine Learning Engineering experience
- 7+ years of professional experience as an ML / software engineer with strong programming skills in Python and C++
- 5+ years of experience as a tech lead, significantly contributing in overarching system design and SW architecture matters
- 5+ year of professional experience of writing and optimizing highly efficient parallel learning and inference code in C++, CUDA or OpenCL
- Experience with deep learning frameworks such as PyTorch, TensorFlow and building deep neural networks in a distributed training environment
- Outstanding documentation, profiling and debugging skills
- Fluent English language skills (oral and written)
Preferred qualification :
First-author publications in the top-notch journals in the field
- Previous experience with high performance computing is a plus
- Prior experience with autonomous driving, sensor fusion or computer vision at scale
- Experience in working with teams focusing on data analysis and optimizing deep net performance
NICE TO KNOW
- Remote work options
- Temporary work from abroad in selected countries
- Flextime / optional working hours
- Company pension plan
- Annual professional development
- Sabbatical option up to 6 months
- 30 days paid + 10 days unpaid leave
- Possibility for VW Group car leasing