1. Develop and evaluate state-of-the-art computer vision algorithms for real-time image analysis.
2. Develop, implement, and optimize analytics and machine learning algorithms
3. Propose and implement creative, efficient solutions for vision and control problems
4. Determine project specifications and project schedule by studying product requirements and
5. specifications, calculating time requirements and sequencing project elements.
6. Documentations for design control.
7. Set up and manage AI development and production infrastructure.
8. Build data ingest and data transformation infrastructure.
9. Identify transfer learning opportunities and new training datasets.
10. Build AI models from scratch and help product managers and stakeholders understand results.
11. Create APIs and help business customers put results of your AI models into operations.
12. Keep current of latest AI research relevant to our business domain
13. Manage the infrastructure and data pipelines needed to bring code to production
14. Build algorithms based on statistical modelling procedures and build and maintain scalable machine learning solutions in production
15. Use data modelling and evaluation strategy to find patterns and predict unseen instances
16. Liaise with stakeholders to analyze business problems, clarify requirements and define the scope of the resolution needed
17. Analyze large, complex datasets to extract insights and decide on the appropriate technique
18. Develop the Machine Learning Model as per the Needs
19. Execute full software development life cycle (SDLC)
20. Develop flowcharts, layouts and documentation to identify requirements and solutions
21. Develop software verification plans and quality assurance procedures
22. Document and maintain software functionality
23. Troubleshoot, debug and upgrade existing systems