Artificial Intelligence Engineer Resume Sample
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William E. Rosser
Data-oriented Artificial Intelligence Engineer, fluent in C++ and Python, with a problem-solving attitude, an introspective attitude to projects, and a solid understanding of banking industry requirements.
- Collaborate with Data Scientists and Product Managers to define an issue statistically and within the scope of the company.
- Devise strategies for tracking and visualizing the effectiveness of all installed methods, and publish verified schemes to the RTB platform.
- Proficient in C/C++ and Java development and troubleshooting skills.
- Understanding of open-source Machine Learning technology.
- Construct models and test the outcomes.
- Assist in the growth, validation, and installation of operational applications.
- Committed to the growth of technologies in IoT safety and helped to increase corporate earnings by 50% in the third quarter.
- Collaborated with other AI specialists in the organisation to design, create, and test software that detects risks and protects IoT systems applying AI and machine learning techniques.
- Rectified difficult obstacles and helped game designers construct without restrictions by recommending technological options to deliver a wealth of experience.
- Helping the R&D division and fast development staff in writing polished, optimized code for numerous games to increase the utilization of basic components.
- Working actively with architects to develop the essential procedures for action games, creating decision trees for various stages, and assisting in the creation of neural nets as applicable.
- Evaluating peers' operational ideas with other computer programmers and coaching junior software engineers and interns as required to improve their talents and efficiency.
- Created a customer classification methodology that resulted in a 45% rise in business total sales.
- Introduced multiple architectures to handle millions of more client data.
- Received 100 percent adherence to business best practices on a continuous basis.
- Revenue was predicted within 1.8 percent using logistic regression frameworks.
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