2x Software Engineer (Geospatial Data)
Mobileye technology analyses imagery from a built-in video camera installed on the device to recognise and extract features that are potential hazards for the vehicle. The system does not record any video, it processes the video feed in real-time, extracting relevant features and these are referenced to a GPS track from the vehicle. This is commonly known as SLAM (simultaneous location and mapping). A small data-packed is transmitted back to Mobileye containing just the features and GPS track. The information that is collected and identified by the vehicle using onboard AI processing is currently predominately street furniture (street lights, roadside cabinets, speed limits, traffic restrictions) and road markings.
Additional capabilities that Mobileye are working on include measuring tree canopy, counting pedestrians and identifying property types and number of floors. Mobileye are also using this data to improve their understanding of vehicle and driver behaviours to further their market positing in the CAV (Connected Autonomous Vehicle) market. All data collected is GDPR compliant.
An internal team have successfully demonstrated the methodology to analyse, extract and geo-reference features captured in the Mobileye RSD (Road Segment Data) files in the 10-vehicle trial using special vehicles. The next phase is to scale up capture and implementation of this process to prove the capability to a wider geographic area while understanding the commercial value of the output with a real commercial client, this client would have invested in the hardware within some of their fleet vehicles.
This will also seek to define and develop a generic fulfilment mechanism for supply of the data back to the commercial client in the first instance but capable of extension for multiple subsequent customers.
Creation of a minimum viable product (MVP) end to end solution capable of supplying product data to a customer with iterative releases in July and October 2019 and January 2020, with project to end 31st March 2020; end to end scope as follows:
i) Receive Data from Mobileye either via Realtime feed or ftp
ii) Provide a processing environment that can run an algorithm for each file. (Expectation is 30 files per vehicle per day, with this scaling up to ~100k vehicles)
iii) An intermediate store for data received and data output from the algorithm for each file. This needs to cope with the volumes outlined above.
iv) Provide a processing environment that can run an algorithm on the database intermediate store
v) A finalised store for storing Single View of the World data
vi) Provision of data for customers (as per below deliverables)
All of the above is subject to change once further analysis and customer engagement is complete. Depending on speed of recruitment and onboarding, work and deliverables will be associated with one of the below delivery phases.
Description of Deliverables:
Phase Summary of Deliverables
Beta Release –October 2019
· Productionise file download delivery system in Azure (ensuring appropriate scalability)
· Establish change and update process for receiving and refreshing customer data
· Develop update notification service for communications to customers
· Scope, shape and design API delivery Develop and create MVP release for API delivery, including API security
MVP Release - January 2020
· Productionise change and update process for receiving and refreshing customer data
· Productionise update notification service for communications to customers
· Production release for API delivery
Understand business requirements and develop the appropriate solution that meets business needs. Your knowledge will encompass a wide variety of techniques and technologies, allowing you to build scalable, performant systems that are easy to maintain and support. Experience around Deployment, Debugging, Testing, Scaling and Monitoring modern cloud-based systems is desired.
Your role will include daily contact with stakeholders and team members. Code should be written using best practices to ensure it is clean and testable. We will encourage you to identify opportunities to maximise development benefit within your team and the abilities to learn quickly and think creatively are essential.
· Experience in designing and implementing solutions using Microsoft Azure cloud services
· Demonstrable skills in Python, using libraries such as Shapely, Pandas, Numpy
· Good knowledge of modern engineering best practice
· Motivated to quickly self-learn and keep up-to-date with modern and relevant techniques
· Excellent communication skills
· Proven track record of working within an AGILE delivery team
· Very good track record in problem resolution and the selection of technical solutions
· Qualified to relevant degree level(or equivalent commercial experience
· Awareness of geospatial systems and technologies is desirable but not essential
Duration of post if applicable: 8 months
IR35 Status: In scope
CANDIDATE WILL NEED TO PROVE THEIR RIGHT TO WORK IN THE UK.