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Which department will you join?
How hard is it to identify vehicles in a picture?
It is not very difficult to identify a normal car, but on the road, we may encounter cases that are not routine.
The challenge our team faces is to correctly identify what meets the definition of a "vehicle" and what does not. The task is challenging since we need to do it within real-time constraints and with great accuracy.
To achieve performance appropriate for a real ride, we use very large amounts of tagged data. Our team's developers face many tasks that include all aspects of work with data:
How do we make sure that the data is clean, varied, and sampled correctly?
How do you take raw data from tagged car ride videos and turn it into examples that go into a neural network?
Once we have good data, we try to get the most out of it. We train a network that generalizes well for cases in the real world
Vehicle identification is critical for any driving-assistance system, so our team is at the core of the company's algorithmic activity. We are at the forefront of development, both in terms of tools and in terms of algorithmic capabilities.
We're hiring a talented Data Engineer to join the Objects Data team!
This position will work directly with our R&D algorithm team to evolve our large scale, high-performance data processing system. We need smart engineers who can pick up and understand complex technical areas quickly - and who are enthusiastic about building new technologies!
How you job As a Data Engineer in Objects Group will look like?
Design, develop, and support a petabyte-scale cloud data system that is highly parallel and fault-tolerant
Build high-quality and highly reliable software to meet the needs of demanding object detection work
Analyze and understand performance and scalability bottlenecks in the system and solve them
Pinpoint problems, instrument relevant components as needed, and ultimately implement solutions
Design and implement the new service architecture required to enable the Mobileye Data Cloud
Develop tools for improving our algorithm developers' workflows
Our Ideal Data Engineer will have:
2+ years industry experience
Fluency in Python
Familiarity with development in a Linux environment
Experience with data modeling and data systems design
Experience with implementation testing, debugging and documentation
Bonus points for experience with the following:
Query optimization, query execution, data warehouse design and implementation
Experience with AWS architectures
Experience with PostrgreSQL
Large-scale data processing solutions like Spark
Large scale distributed systems, streaming applications
Big data storage technologies and their applications, e.g. Columnar Databases, NoSQL, etc