Data Engineer and Team Manager

Autobrains is a fast-growing start-up with a groundbreaking approach to unsupervised learning and signature-based data representation that is set to disrupt the next generation of vehicles and mobility.

At Autobrains, you will face never-ending intellectual challenges as we redefine AI for scalable autonomous platforms and products, with the goal to forever change driving and make the roads a safer place for all. You will work with bright and talented people, in an environment where professional and personal development are a top priority.

Autobrains is backed by top investors and key players in the automotive industry such as Temasek, Toyota, BMW, Continental, Vinfast and Knorr-Bremse, with headquarters at the heart of Tel Aviv.

Requirements:

BSc in EE or Computer Science, Industrial Engineer (or similar field) (MSc – advantage)
Know-how in processes and organizational techniques
Experience in heading up exceptionally large-scale business process operations.
Familiar with Data transfer methodologies design and operation
Strong project management skills: experience in working with cross-organizational teams- R&D, IT, Product, and project managers to achieve various project goals in an effective and timed manner.
Ability to handle multiple competing priorities in a fast-paced environment
Experience in big data, database techniques, tagging, and labeling – advantage.
Experience as a first-line manager (advantage)
Experience in Computer Vision products – advantage
Experience in data architecture, especially from the automotive industry – big advantage.

Responsibilities:

The Data engineer is responsible for the definition of the data ecosystem used by the object detection team Autobrains.
Overseeing the company’s data pipeline system and processes including organizing, storing, labeling, and analyzing the data received, to ensure timely delivery of high-quality data required for the development projects of the company.
Establish and implement an effective process for data management, and build a strong team of data annotation specialists.
Data team management: group management, monitoring data tasks, monitoring of the work pace and improving processes to ensure efficient processes
Working closely with R&D and product management teams, algorithms, functional testing specialists, and data tagging professionals to ensure successful kickoff and execution of required projects including manpower planning, the correct definition of requirements, training materials preparation, and progress follow-up.
Provide Data for training deep learning networks.
Collect and analyze data for the effectiveness of the projects, using scripts, python queries, and building dashboards
Test new annotation tools and improve existing ones, validate the quality of the annotated data.