Job Responsibilities
1. Build and maintain mechanisms for running model inference.
2. Collaborate with other teams to transition new models from design to production efficiently.
3. Make technical decisions balancing performance and cost.
4. Contribute to best practices, design patterns, and code refactoring opportunities.
5. Ensure the full video pipeline is efficient through cross-team collaboration.
6. Maintain the CI/CD pipeline for rapid deployment of models.
7. Build and maintain inference edge devices and monitoring tools.
8. Support other Vision Engineers in understanding existing design concepts.
9. Maintain documentation to facilitate further development of inference components.
10. Participate in team process improvements and create mechanisms for deploying models across multiple targets.
11. Work with the team lead to define data requirements and influence technical decisions from problem statement to solution.
12. Ensure new algorithm ideas are delivered into production in collaboration with internal stakeholders.
13. Create prototypes to achieve business objectives and key results (OKRs).
14. Assist the technical operations team with onboarding and adapting farm installations.
15. Develop new methods to run algorithms effectively.
Your Profile / Qualifications
* Degree in Computer Science or a related computer vision discipline.
* Experience taking models from creation to production.
* Experience working with academics/researchers to convert ideas into products.
* Comprehensive understanding of model inference.
* Experience with both cloud inference and edge inference devices.
* Proficiency in Python.
* Understanding of image and video processing.
* Driven by high performance.
* Eager to stay up-to-date with the latest technologies.
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