Deep Learning Engineer, Cluj/Bucharest

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.

• You have a university degree in computer science, automation, electronics and telecommunications, informatics, mathematics or comparable
• You have a thorough understanding of deep learning / machine learning (i.e., building blocks, mathematics, and intuition behind)
• You have experience with Python and with a deep learning training framework (TensorFlow, PyTorch, etc.)
• You enjoy working on both research & development related activities
• You are motivated and committed to get involved, learn and contribute to the development of cutting-edge technologies in collaboration with a global network of experts
• You have good communication, strong analytical skills, you are team oriented, have initiative, perseverance, and attention to details
• You are self-organized and able to estimate, prioritize and schedule own tasks
• You are result and quality oriented

Nice to have:

• Experience with deep learning-based multi-task perception
• Experience with non-learning-based algorithms (i.e., 3D computer vision, optical flow, tracking etc.)
• Experience with C++ (for model deployment, re-simulation, pre/post processing)
• Experience with developing automated driving systems
• Experience with software design on embedded systems
• Knowledge of embedded software optimization and parallelization (ex: NEON, DSP) for real-time performance
• Experience with software documentation, tracking (ex: Jira) and versioning tools
• Not even the slightest desire to develop any kind of web design / java project

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 a team of engineers that harness the power of artificial intelligence and deep learning to create industry leading automated driving technologies. We develop state-of-the art neural networks based on video sensors, with the focus on the traffic / driving scenes understanding. Our activities cover the entire data-driven development loop, ranging from data selection and filtering to creating models for various vision tasks and to optimizing & deploying them on embedded automotive hardware, for various mobile platforms (vehicles, trains, motorcycles etc.). Join us in our deep learning revolution! 

In your role you will:

• Create, adapt and train deep learning models that detect / classify / segment objects of interest in the context of automated driving, such as, but not limited to: vehicles of all types, pedestrians, road infrastructure elements, traffic lights, signs, free-space etc.
• Be responsible for the data-engineering related activities such as data filtering and automatic search, doing statistics, defining labeling guidelines, preparing the data requirements for each model etc.
• Be responsible for optimizing and deploying trained deep learning models to dedicated hardware devices
• Evaluate and validate the performance of the models based on ground truth and reference sensors data, and will experiment ways to improve scenarios with undesired behavior

Technology Stack:

• Python, C++
• TensorFlow, Keras, PyTorch
• MATLAB, OpenCV
• NEON
• Horovod, Microsoft Azure, Nvidia CUDA
• Linux
• GIT, Jira, Bitbucket