Responsibilities / Tasks
Responsible for building and maintaining the mechanisms for running model inference.
Work with other teams to get new models from design to production as efficiently as possible.
Make technical decisions that balance performance and cost.
Contribute to best practices, design patterns and identifying opportunities to refactor code.
Collaborates across team to ensure the full video pipeline is efficient.
Maintaining the CI/CD pipeline to ensure rapid deployment of models.
Take an active role in building, maintaining the inference edge device along with the tools required to monitor it in the field.
Support other Vision Engineers in learning existing design concepts.
Maintain documentation to allow others to further develop inference components.
Innovation and Change:
Plays an active roles in team process improvements.
Creates and maintains mechanisms to deploy models across multiple deployment targets.
Work with the team lead to scope and refine data requirements and to influence technical decisions, from problem statement to delivered solution.
Works with internal stakeholders to ensures to makes sure new algorithm ideas get delivered into production.
Creates prototypes that help achieve business Objectives and Key Responsibilities (OKR’s).
Works with technical ops team to help on board and adapt farm installs where required.
Create new ways to run algorithms effectively.
Your Profile / Qualifications
Degree in Computer Science or related computer vision based discipline.
Experience taking models from creation to production.
Experience working with academic / researcher to convert ideas to products.
A comprehensive understanding of model inference.
Has worked with both cloud inference and edge inference devices.
Detailed knowledge of Python
Attention to detail.
Understanding of image and video processing.
Driven by high performance.
Eagerness to stay up to date with latest technologies.
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