Job Title: Computer Vision Engineer
Location: Tunbridge Wells - Hybrid
About us:
VisionTrack is a multiple award winning IOT, high throughout / big data insurance telematics & video solution.
Role:
We are looking for developers with experience in computer vision applications to join one of our agile development teams. We try to avoid silos of knowledge so the role will involve working in all areas of the solution but with more emphasis on computer vision applications deployed on our Autonomise cloud platform. We are looking for someone who can fit into this way of working, so knowledge in Agile / DevOps working practices, including SCRUM, Continuous Integration & Continuous Delivery and someone who can follow and promote best practices in these areas is essential.
Essential Skills:
- .NET
- C#
- Mvc (Framewrk and/or Core)
- WebApi
- SignalR
- Python programming experience
- Previous experience in the development and use of Convolution Neural Networks (CNN’s) for machine vision and image analysis applications
- Experience with large-scale data sets
- Experience with open source machine learning platforms such as Keras / tensorflow or PyTorch
- Ability to develop using rapid prototyping techniques aimed at demonstrating applications quickly in a fast moving environment.
- Agile / DevOps
- Familiarity f SCRUM
- Familiarity f DevOps Continuous Integration / Continuous Delivery practices.
Desired Skills:
- Azure
- Azure Functins / Serverless Architecture / Microservices
- Sql Database’s
- EventHub
- Redis
- CsmosDb, or other NoSql Db’s
- Autmation, Powershell / ARM templates
- Applicatin Insights
- Azure Search
- Resiliency - Availability Sets, Availability Znes, Region Paris
- IOT expereince
- DevOps CI/CD working / best practices. Automation first approach.
- TeamCity, Octopus Deploy
- Git, including GitFlow & Pull Requests / Peer Reviews.
- ReactJs, Jest, ESLint, Sinon, Npm, Webpack
- Working with Geospatial data.
- Azure Big Data technologies, DataLake, Sql Data Warehouse, Azure Databricks
- Media Decoding
- Academic background in a scientific or technical discipline with some formal computer vision / machine learning content.